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    Information & Control
    EEGs Feature Induced by Person’s Information Based on Directed Network
    CHANG Wen-wen, WANG Hong, HUA Cheng-cheng, WANG Qiao-xiu
    2019, 40 (1):  1-6.  DOI: 10.12068/j.issn.1005-3026.2019.01.001
    Abstract ( 744 )   HTML   PDF (1004KB) ( 860 )  
    Based on the visuo-auditory information of acquaintances and strangers, the possible differences of the cognitive mechanisms were studied by recording EEG signals. Firstly, the ERP signals for different stimuli types were obtained by recording the EEG signals of visuo-auditory stimuli. Then, the directed functional network was constructed by calculating the phase transfer entropy. Finally, network parameters for the key connection were analyzed. The results show that compared with the directed network induced by unfamiliar information, the role of key nodes in the network of familiar information is strengthened, as well as the aggregation ability. The connections of the familiar network tend to be more global, and the information exchange between different brain regions are increased, which is good for the identification of the familiars.
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    Fast Image Segmentation Algorithm Based on Parametric Level Set Active Contour Model
    CHEN Hong, YU Xiao-sheng, WU Cheng-dong, SUN Peng
    2019, 40 (1):  6-10.  DOI: 10.12068/j.issn.1005-3026.2019.01.002
    Abstract ( 771 )   HTML   PDF (746KB) ( 797 )  
    In order to improve the segmentation speed, a fast image segmentation method based on parametric level set active contour model was proposed. The level set function was determined by the parameter vector, rather than the signed distance function, which reduces the dimension of the level set function. The parametric level set function was embedded into the classical LGDF(local Gaussian distribution fitting) segmentation algorithm, and it does not need to be re-initialized or additional regular terms, and it can choose larger step length. The experiment results show that the proposed method can effectively segment medical images such as ultrasound, CT and MR medical images. Compared with the LGDF model with regular terms and the recently proposed fast segmentation algorithm MSLCV, in the case of similar segmentation accuracy, the calculation speed of the proposed method is improved obviously.
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    Random Forest Based Quality Analysis and Prediction Method for Hot-Rolled Strip
    JI Ying-jun, YONG Xiao-yue, LIU Ying-lin, LIU Shi-xin
    2019, 40 (1):  11-15.  DOI: 10.12068/j.issn.1005-3026.2019.01.003
    Abstract ( 733 )   HTML   PDF (423KB) ( 831 )  
    The process data of hot-rolled strips from an iron and steel enterprise were analyzed to find out the inherent relationship between process parameters and production quality by using an improved random forests algorithm. After critical features being extracted, a defect prediction model was built. According to the experiment, balancing operation can improve the prediction accuracy of the imbalanced data sets. Meanwhile, the combination of CART and C4.5 can further improve the prediction accuracy than each single method. Furthermore, in consideration of the characteristics whose features have high or low correlations with the response variable, mutual information was introduced as an evaluation criterion for feature selection. Mutual information makes great contribution to classification effect of random forest algorithm, and recognition rate of defects of hot-rolled strips is obviously improved by using three strategies.
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    Improved Low Complexity Amplitude and Phase Estimation Beamforming Algorithm
    ZHANG Shi, SHE Li-huang, YAN Xin
    2019, 40 (1):  16-20.  DOI: 10.12068/j.issn.1005-3026.2019.01.004
    Abstract ( 649 )   HTML   PDF (640KB) ( 654 )  
    To improve the imaging quality in the minimum variance method of low complexity, an improved low-complexity amplitude and phase estimation beamforming algorithm was proposed. The adaptive weighted value was calculated by extracting the effective rows of the covariance matrix, where the selection of the effective number of rows was determined by a more accurate Gaussian phase coherence coefficient, which was then used to modify the weighting vector in order to reduce the complexity and ensure the quality of the imaging at the same time. Through experimental verification, the improved algorithm was compared with the original algorithm and another beamspace method to reduce the complexity, which fully proves the superiority of the improved algorithm in reducing the complexity and improving the imaging quality.
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    Adaptive Caching Algorithm Based on Adaboost Learning for Information Centric Networking(ICN)
    CAI Ling, WANG Jin-kuan, WANG Xing-wei, HU Xi
    2019, 40 (1):  21-25.  DOI: 10.12068/j.issn.1005-3026.2019.01.005
    Abstract ( 643 )   HTML   PDF (567KB) ( 651 )  
    In order to optimize the cache placement in ICN(information centric networking), an ACAL(adaptive caching algorithm based on Adaboost learning) algorithm was proposed. According to the algorithm, first, the extracted data flow including node data and content data was employed as the network resources, then the ensemble learning algorithm Adaboost was used to analyze and mine the data flow, and the mapping relationship between the state attribution data and the matching relationship value was utilized to predict the matching relationship between the node and the content in next period. Finally, the matching relationship algorithm was used to guide the cache placement. The simulation experiments demonstrate that the proposed ACAL, compared with CEE, LCD, prob0.5 and OPP yields a significant performance improvement, such as delay, hit rate and average link utilization.
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    Anomaly Detection of Network Traffic Based on Flow Time Influence Domain
    XU Jiu-qiang, ZHOU Yang-yang, WANG Jin-fa, ZHAO Hai
    2019, 40 (1):  26-31.  DOI: 10.12068/j.issn.1005-3026.2019.01.006
    Abstract ( 744 )   HTML   PDF (805KB) ( 797 )  
    Aiming at improving the accuracy rate of anomaly network traffic detection, a network traffic detection model was proposed based on the time influence domain(TID)of network flow. By analyzing the changes of average degree of traffic network model under the normal and abnormal conditions, an anomaly detection algorithm of network traffic based on the average degree metric of complex network was developed to detect the abnormal traffic. Experimental results show that based on the flow time influence domain, the anomaly detection model of traffic network can reasonably describe the inter-dependency relationship between network traffic. The proposed method has a better detection performance, meanwhile only three network features, i.e. timestamp, source IP and destination IP, are needed to implement the above model. Detection efficiency is better than other methods. The method proposed meets most network types and has a better ubiquity.
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    Materials & Metallurgy
    Decomposition Behaviors of Retained Austenite in Hot Rolled TRIP Steels During Isothermal Treatments
    WANG Xiao-hui, KANG Jian, YUAN Guo, WANG Guo-dong
    2019, 40 (1):  32-37.  DOI: 10.12068/j.issn.1005-3026.2019.01.007
    Abstract ( 713 )   HTML   PDF (2450KB) ( 904 )  
    Scanning electron microscopy(SEM), transmission electron microscopy(TEM), X-ray diffraction(XRD) and tensile tests were used to investigate decomposition behaviors of the retained austenite(RA) in hot rolled TRIP steels with low Si and some Al elements during isothermal treatments. The results show that during different isothermal temperature, the RA can decompose into ferrite and carbides gradually with the isothermal time. When the isothermal temperature increases, the time required for the RA decomposition decreases. At different isothermal temperature, the variation tendency of tensile strength, total elongation and strength ductility balance of the tested steel decreases with the isothermal time. With different isothermal treatments, the variation of the volume fraction of the RA tends to be decreased, while the carbon content has little effect.
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    On-Line Correction Strategy for Processing Temperature in Ultra-fast Cooling System Under Variable Velocity Rolling
    LI Zhen-lei, CHEN Dong, YUAN Guo, WANG Guo-dong
    2019, 40 (1):  37-42.  DOI: 10.12068/j.issn.1005-3026.2019.01.008
    Abstract ( 724 )   HTML   PDF (934KB) ( 576 )  
    Based on the ultra-fast cooling system of a certain plant, the effect of various velocity of hot-rolled strip on the transfer coefficient and cooling time was analyzed. According to the velocity mechanism during producing, on-line corrected control strategy of velocity was developed and the calculated velocity is accurately matched the measured value. Based on the above strategies above, an on-line correction strategy for processing temperature was developed to eliminate the influence of velocity fluctuation on temperature deviation so that the accuracy to control processing temperature was improved. By proposing such on-line correction strategy to an on-site operation, the ultra-fast cooling delivery temperature and coil temperature can be well controlled, the temperature deviation affected by velocity fluctuation is effectively eliminated, and the hit rate of process temperature is more than 96%, which lays solid foundation for new product development and mass industrialized production.
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    Constitutive Equations for Moderate-Temperature Deformation of Fe-6.5%Si Steel
    MEI Rui-bin, BAO Li, LI Chang-sheng, LIU Xiang-hua
    2019, 40 (1):  43-47.  DOI: 10.12068/j.issn.1005-3026.2019.01.009
    Abstract ( 678 )   HTML   PDF (1010KB) ( 735 )  
    Using Gleeble 3500, the deformation behaviors of a single-pass compression for Fe-6.5%Si steel at temperature ranging from 300 to 600℃ and strain rate ranging from 0.05 to 5s-1 were studied. The flow stress increases dramatically at initial uniform plastic deformation stage due to work hardening, while the increment of flow stress is to be weakened during further deformation when the dynamic softening occurs. The strain hardening index decreases with increasing the temperature and decreasing the strain rate. A new constitutive model of Fe-6.5%Si steel at moderate-temperature deformation was proposed through describing the strain hardening index as the function of temperature and strain rate. The results predicted by this model are in good agreement with the experimental data, with an average relative error about 5.35%.
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    Experimental Study on Oxidation and Reduction Reactivity of Cu/Mn Composite Oxygen Carriers
    WANG Kun, LIU Jin-lin, YU Qing-bo, LUAN Wei-peng
    2019, 40 (1):  48-52.  DOI: 10.12068/j.issn.1005-3026.2019.01.010
    Abstract ( 657 )   HTML   PDF (606KB) ( 751 )  
    Cu/Mn composite oxygen carriers were prepared using ZrO2 as binder and the influences of gas flow rate, temperature, inlet oxygen concentration, particle diameter on the oxidation and reduction reactivity of Cu/Mn composite oxygen carriers were examined in a fixed-bed reactor. The results showed that the reduction and oxidation rates increase with the increase of gas flow rate. High temperature favors the reduction, but restricts the oxidation of the Cu/Mn composite oxygen carriers. In the reduction stage, lower oxygen concentration leads to higher reduction rate. However, in the oxidation stage, oxidation rate increases with the increasing of oxygen concentration. For the composite oxygen carriers with different particle diameters, big particle diameter favors both the reduction and oxidation rates.
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    Effects of Operation Parameters on Heat Transfer in Shaft Furnace for Vanadium Titano-Magnetite Roasting
    LUO Xu-feng, ZHANG Sheng, SUN Yong-jun, DONG Hui
    2019, 40 (1):  53-58.  DOI: 10.12068/j.issn.1005-3026.2019.01.011
    Abstract ( 670 )   HTML   PDF (868KB) ( 709 )  
    With a shaft furnace of 2×104 tons annual capacity for vanadium titano-magnetite roasting as the research object, a three-dimensional steady-state heat transfer mathematical model of shaft furnace was established. The reaction heat was complied into solid phase energy equation in the form of internal heat source by UDF and the pellet velocity was defined. The roasting time and temperature were used as the evaluation indexes in order to study the effects of operation parameters on heat transfer performance. The results show that the roasting and cooling air volume rates and the pellets velocity are three main factors and the influence of the last one is the largest. Under the conditions of 38mm pellet diameter, 4~6h roasting time and 1100~1200K roasting temperature, the suitable operating parameters are obtained as: the cooling air volume rate is 1210~1430m3/h; the roasting air volume rate is 3070~3670m3/h; and the moving down velocity of pellets is 0.258~0.290m/h.
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    Interface Characteristics of Lead and Copper Minerals from Ultra-fine Cyanide Tailings
    QIU Xue-min, YANG Hong-ying, CHEN Guo-bao, ZHAO Su-xing
    2019, 40 (1):  58-62.  DOI: 10.12068/j.issn.1005-3026.2019.01.012
    Abstract ( 754 )   HTML   PDF (1246KB) ( 751 )  
    The copper-lead separation of cyanide tailings from Shandong Province is hardly possible in the process of flotation. XRD, laser partide size analyzer, flotation experiment, FTIR, SEM-EDS and microscope are used to investigate the interface characteristics of lead and copper minerals. The results show that the main minerals in the cyanide tailings are galena, chalcopyrite, pyrite and sphalerite. The mineral particles smaller than 38μm account for 95.61%. The surface of chalcopyrite and galena in the cyanide tailings contains plenty of oil component and it is proved to be lubricating oil. Chalcopyrite is covered with lubricating oil and isn’t inhibited by cyanide. Ultra-fine galena particles are wrapped on the surface of chalcopyrite by hydrophobic force, and this makes the lead and copper unable to be separated.
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    Mechanical Engineering
    Vibration Response Analysis of Fiber-Reinforced Composite Thin Shell Based on Multilevel Correction Technique
    LI Hui, ZHOU Zheng-xue, WU Teng-fei, HAN Qing-kai
    2019, 40 (1):  63-69.  DOI: 10.12068/j.issn.1005-3026.2019.01.013
    Abstract ( 649 )   HTML   PDF (1012KB) ( 689 )  
    The vibration response of fiber-reinforced composite thin shell was analyzed based on the multilevel correction technique. Firstly, the theoretical model was established by considering the influence of fiber orientation, and the vibration response was solved by using the Ritz method. Next, the more precise theoretical model of composite thin shell was obtained by using the multi-level correction technique and the experimental data. Finally, T300 fiber/epoxy composite thin shell was taken as the study object and the laser scanning test system was set up to obtain the first 6 natural frequencies, modal shapes and vibration responses. By comparing the experimental resonant response results with the calculated results after adopting the multilevel correction technique, it was found that the calculation error is in the range of 5.2%~14.3%, which is within an acceptable level, and thus the correctness of the above analytical method was verified.
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    Vehicle Driving State Estimation of the Adaptive Soft-Sensing Algorithm
    HAO Liang, GUO Li-xin
    2019, 40 (1):  70-76.  DOI: 10.12068/j.issn.1005-3026.2019.01.014
    Abstract ( 655 )   HTML   PDF (943KB) ( 741 )  
    The low-cost measurement of vehicle driving states is realized by establishing an algorithm based on the traditional unscented Kalman filter(UKF) which can estimate vehicle driving state parameters and the sub-optimal Sage-Husa noise estimator which can effectively solve the problem of noises varying with time. Meanwhile three-degree-of-freedom(3-DOF) dynamic model of electrical vehicles and highway safety research institute(HSRI) tire model are established. Accordingly, electrical vehicle driving states can be accurately estimated by fusing the low-cost measurement information of longitudinal and lateral acceleration and handwheel steering angles. Under the selected typical working condition, the adaptive unscented Kalman filter(AUKF) soft-sensing algorithm is compared with the UKF soft-sensing algorithm, and the hardware-in-the-loop(HIL) testing platform result indicates the AUKF soft-sensing algorithm has a good performance in robustness and is able to realize the effective estimation of electrical vehicles’ driving state more precisely than the UKF soft-sensing algorithm.
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    Construction of Driving Cycle Based on Big Data and Markov Chain
    CAO Qian, LI Jun, LIU Yu, QU Da-wei
    2019, 40 (1):  77-81.  DOI: 10.12068/j.issn.1005-3026.2019.01.015
    Abstract ( 802 )   HTML   PDF (561KB) ( 1048 )  
    In order to improve the accuracy of typical driving cycle, the constructing algorithm for typical driving cycle was studied. 10 passenger cars in Shenyang City were selected to collect the driving data by autonomous driving, and the big sample database was established. Firstly, the raw data was filtered for noise reduction by using Fourier transform method. Secondly, the modified Kneser-Ney smoothing method was applied to compute the state transfer probability matrix, and the driving cycle constructing algorithm based on Markov chain was proposed. Finally, the typical driving cycle for passenger cars in Shenyang City was constructed and compared with the overall characteristics of the database. The results showed that the average deviation between the constructed cycle and the database population is 2.46%, the deviation values of all the characteristic parameters are within 10%, and the validness of the proposed algorithm is thus verified.
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    Quantitative Analysis of Fracture Surface Defect and Its Effect on Strength of Connecting Rod
    SHI Zhou, KOU Shu-qing
    2019, 40 (1):  82-87.  DOI: 10.12068/j.issn.1005-3026.2019.01.016
    Abstract ( 614 )   HTML   PDF (1283KB) ( 802 )  
    The fracture joint surface was obtained by the fracture-split test and the fracture surface was reconstructed by reverse engineering. The connecting rod model with defect was built. The quantitative description of the fracture surface defect was realized. The effects of fracture surface defect of different sizes and positions on the strength of the connecting rod were explored, and the control standard of the relevant dimension in the processing process was formulated. The rules were obtained: with the defect size increasing, the stress of the connecting rod increases gradually and the strength of the connecting rod decreases. When the defect area is larger, the influence on the stress of the connecting rod becomes more significant. The stress of the connecting rod is greater when defect is inside the joint surface than that at the edge of the joint surface. In order to ensure the strength of the connecting rod, the defect size should meet: defect on edge, when 1.5mm<b<2.5mm, a≤-1.125b+5.0875; in-plane defect, when 1.4mm<b<2.1mm, a≤-1.143b+4.8.
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    Theoretical Calculation Method of Volume Flow Rate of Cooling Fans Based on Blade Element-Momentum Theory
    XIE Yi, ZHENG Biao, CHEN Gang, LI Kui-ning
    2019, 40 (1):  88-94.  DOI: 10.12068/j.issn.1005-3026.2019.01.017
    Abstract ( 917 )   HTML   PDF (1059KB) ( 1241 )  
    A theoretical model that shows the correlation of geometry parameters of cooling fans, rotation speed and volume flow rate was established by using the classic blade element-momentum theory of wind turbines for the axial cooling fan of vehicles. This model revised the load direction on the blade element of blade element-momentum and the inlet and outlet boundary conditions and so on, based on the difference of energy transfer between cooling fans and wind turbines. Then, the experiment and simulation based on computational fluid mechanics were carried to test the precision of the theoretical model for the volume flow rate of cooling fans. The results showed that the theoretical computational method for volume flow rate of cooling fans not only reflects the change of volume flow rate with the rotation speed of fans, but also has high calculation precision. In the researched model, the average relative error between the theoretical calculation method and experiment is 3.57%, and the one between the theoretical calculation method and CFD is 5.03%.
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    Resources & Civil Engineering
    Pre-enrichment Behaviors of Low-Grade Donganshan Iron Ore Using Magnetic Separation
    YU Jian-wen, HAN Yue-xin, LI Yan-jun, GAO Peng
    2019, 40 (1):  94-98.  DOI: 10.12068/j.issn.1005-3026.2019.01.018
    Abstract ( 721 )   HTML   PDF (960KB) ( 890 )  
    A pre-enrichment process of low-intensity magnetic roughing followed by high-gradient magnetic scavenging was proposed, and the effects of magnetic field intensity and grinding fineness on pre-enrichment behaviors of low-grade(w(TFe)=34.60%) Donganshan iron ore simultaneously containing hematite, magnetite and a bit of siderite were studied by XRD, chemical phase analysis of iron, and scanning electron microscope(SEM). The results showed that the optimized grinding fineness of raw ore was 70% passing 0.074mm, the magnetic field intensity for roughing, scavenging Ⅰ and Ⅱ were 120mT, 300mT and 800mT, respectively. Under the optimized conditions, a magnetic pre-concentrate assaying 42.67% iron (mass fraction) with an iron recovery of 95.45% was achieved. The analyses revealed that ferromagnetic magnetite was enriched in low-intensity magnetic concentrate, and weakly magnetic hematite and siderite were recovered successfully by high-gradient magnetic separation. However, some ultra-fine hematite particles(<10μm) were lost in tailing due to their weak magnetic trapping force.
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    Safety Assessment of Bridges Based on Variable Weight and D-S Evidence Theory
    LIANG Li, SUN Shuang, LI Ming, LI Xin
    2019, 40 (1):  99-103.  DOI: 10.12068/j.issn.1005-3026.2019.01.019
    Abstract ( 601 )   HTML   PDF (498KB) ( 806 )  
    The safety assessment of bridge structures can be affected by multi-source factors such as environmental erosion, material aging and external loads. Using single index to evaluate the safety of bridges is prone to misjudgment. Therefore, a multi-factor bridge safety assessment method based on information fusion was proposed. In this method, the variation region of each influence factor was first determined; then the mechanical indexes were extracted through numerical analysis under various load cases; and then the information entropy and fuzzy analytical hierarchy process were utilized to determine the variable weights of index and the grade criterion of single index so as to acquire the basic probability assignment function. The Dempster combination rules was used to determine the fusion safety level and establish the prior database of bridge safety assessment. The proposed method was applied to the safety assessment of a pre-stressed concrete continuous bridge, and the results showed that the proposed method is objective, reasonable and applicable to engineering practice.
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    Improvements of the Directional Total Horizontal Derivatives and Their Application in Edge Detection
    HOU Zhen-long , WANG En-de , TANG Shui-liang, YUAN Yuan
    2019, 40 (1):  104-108.  DOI: 10.12068/j.issn.1005-3026.2019.01.020
    Abstract ( 794 )   HTML   PDF (1617KB) ( 667 )  
    An improvement was made on the basis of directional total horizontal derivative to increase the edge detection resolution in the gravity exploration and enhance the ability of dividing and detecting geological body boundary. Six new kinds of edge detectors were presented, including the vertical derivative of directional total horizontal derivative and enhanced directional total horizontal derivative, directional total horizontal derivative and its vertical derivative integrated in x, y and z direction, which are based on gravity gradiometry data. Through the theoretical model and noise test, it is proved that the improved methods have the good ability for boundary division. Compared with the ordinary ones, the detected edges agree well with that from the model. The real data from Vinton Dome are introduced into the proposed methods and the edges of underground cap rock are recognized more clearly, and the feasibility of the proposed methods is verified.
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    3D Modeling for Heterogeneous Rock Based on LSM and Characteristics of Hydraulic Fracture Propagation
    LI Ming, SHI Yi-tao, LI Xin, LIANG Li
    2019, 40 (1):  109-114.  DOI: 10.12068/j.issn.1005-3026.2019.01.021
    Abstract ( 672 )   HTML   PDF (4203KB) ( 712 )  
    The level set method(LSM)was introduced to describe the static material interface in a rock material. The finite element modeling procedures for the three-dimensional rock sample with the layered feature, randomly distributed inclusions and statistical Weibull distribution heterogeneity were given via the LSM. To study the propagation of hydraulic fracture, a smeared crack model based on the fully coupled, elasto-plastic, pore pressure-solid phase interaction theory was coupled to the LSM. The Corey relation and relative permeability were adopted to calculate the viscosity and permeability of mixture in the smeared cracked hydraulic fracture model. Finally, a case study that simulating hydraulic fracture propagation was carried out in a heterogeneous rock sample following Weibull distribution. The development of equivalent crack zone, pore pressure versus injection time and the effective stress path in the injected element were discussed. The simulation results indicate that the LSM coupling with smeared crack model can be well used for modeling the heterogeneity of three-dimensional rock material and simulating the hydraulic fracturing.
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    An Improved AFSA-Elman Slope Displacement Prediction Network
    WANG Shu-hong, REN Yi-peng, XING Guan-hua
    2019, 40 (1):  115-120.  DOI: 10.12068/j.issn.1005-3026.2019.01.022
    Abstract ( 653 )   HTML   PDF (836KB) ( 686 )  
    In the prediction of slope displacement sequence, there is no specific conclusions on the number of neurons and thresholds in the Elman network hidden layer. The convergence speed is slow, and it is easy to fall into the local solution. Based on this, the improved AFSA-Elman slope displacement prediction network was established by combining the artificial fish swarm algorithm with the Elman network. In order to improve the prediction accuracy and convergence speed of Elman network, the step size of artificial fish swarm algorithm was modified and the initial weights and thresholds of Elman network were optimized by using the powerful optimization ability of the improved fish swarm algorithm. The improved AFSA-Elman network was compared with the traditional Elman network and AFSA-BP network, and the iterative process of the three networks was simulated. The result found that the improved AFSA-Elman prediction network has higher precision and convergence speed than those of the above two prediction network, and it is more suitable for the prediction of slope displacement.
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    Effects of High-Silicon Iron Tailings on Carbonation and Sulphate Corrosion Resistance of Concrete
    CHENG Yun-hong, HUANG Fei, QI Shan-shan, LI Wen-chuan
    2019, 40 (1):  121-126.  DOI: 10.12068/j.issn.1005-3026.2019.01.023
    Abstract ( 664 )   HTML   PDF (764KB) ( 910 )  
    Concrete can be prepared by using the mechanochemically activated high-silicon iron tailings as an auxiliary cementing material to partially substitute cement. An experimental study was conducted to investigate the effects of tailings on resistance of concrete to carbonation and sulfate corrosion. Results show that when the substitution ratio is 10%, 20%, 30% and 40% respectively, the carbonation resistance of concrete becomes worse with the increasing of the substitution ratio, but still can meet the practical requirements of concrete structure; however, the sulfate corrosion resistance of concrete presents an upward trend with the increasing of the substitution ratio; when the substitution ratio is 20%, 30% and 40% respectively, the sulfate corrosion resistance of concrete is superior to the normal group. It is feasible to use mechanochemically activated high-silicon iron tailings as an auxiliary cementing material to prepare concrete.
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    Mechanism of Thermal Effect of Ultrasonic Cavitation on Excess Sludge Disintegration
    YOU Mei-yan, ZHANG Xiu-xiu, SHEN Yang, ZHU Tong
    2019, 40 (1):  126-131.  DOI: 10.12068/j.issn.1005-3026.2019.01.024
    Abstract ( 709 )   HTML   PDF (760KB) ( 705 )  
    To ascertain the thermal effect of ultrasonic on disintegrating excess sludge, ultrasonic and water bath heating were used to treat organic macromolecules, bacteria and excess sludge. Results show that the TC and TOC content of acid orange are decreased after ultrasonic treatment, which proves the hyperthermia pyrolysis effect. The ultrasonic disintegrating effects on bacteria and excess sludge in three cases can be compared as: ultrasonic under no recirculating cooling water > ultrasonic under recirculation cooling water > water bath heating. The results show that ultrasound thermal effects can promote the disintegration of bacteria and the excess sludge. When the excess sludge is disintegrated, the temperature rise caused by energy from ultrasonic cavitation effect accounts for more than 10% of the total ultrasonic energy. When the temperature is up to 70℃, the contribution of ultrasonic heat to the excess sludge is about 20%.
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    Management Science
    Research on Manufacturer’s Innovation Decision Making from the Perspective of Retailers’ Scale Differences
    LI Kai, GUO Xiao-ling
    2019, 40 (1):  132-137.  DOI: 10.12068/j.issn.1005-3026.2019.01.025
    Abstract ( 646 )   HTML   PDF (484KB) ( 634 )  
    The vertical relationship of supply chain was selected as the research background, and a vertical market structure was constructed, consisting of a monopolistic manufacturer and two competing retailers. The two-stage game model was used to study the effect of buyer power caused by the downstream retailer’s scale differences on the upstream manufacturer’s technological innovation decision. The results show that the enhancement of the downstream large-scale retailer’s buyer power can effectively promote the innovation of the upstream manufacturer; at the same time, the retailer’s product price and the upstream manufacturer’s profit will decrease along with the enhancement of buyer power. However, the impact on the wholesale price is uncertain, which mainly depends on the strength of buyer power. When the buyer power is weak, the manufacturer will increase the small-scale retailer’s wholesale price along with the enhancement of large-scale retailer’s buyer power. When the buyer power is strong, the upstream manufacturer will decrease the small-scale retailer’s price along with the enhancement of large-scale retailer’s buyer power.
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    Method for Product Purchasing Recommendation Ranking Based on Multi-attribute Online Ratings Information
    ZHANG Jin, YOU Tian-hui, FAN Zhi-ping
    2019, 40 (1):  138-143.  DOI: 10.12068/j.issn.1005-3026.2019.01.026
    Abstract ( 754 )   HTML   PDF (356KB) ( 736 )  
    In order to support consumers’ purchasing decision, a product purchasing recommendation ranking method based on multi-attribute online ratings information was proposed. First, the online rating information on each product attribute was transformed into the probability distributions of attribute rating scales, and the cumulative distribution functions of online evaluation results to each product attribute were obtained. Then, the weighted cumulative distribution functions decision matrix was constructed, and the weighted cumulative distribution vectors of the ideal and anti-ideal products were determined based on the decision matrix. Furthermore, the distances between the weighted cumulative distribution vectors of each alternative product and the ideal/anti-ideal product were calculated, and the closeness coefficient of each alternative product was obtained. According to the closeness coefficient, the recommendation ranking results of alternative products were determined. Finally, an example to support consumers’ car purchasing decision was used to illustrate the feasibility and validity of the proposed method.
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    Inter-regional Transfer Decision Making of Polluting Enterprises Based on Environmental Regulation
    ZHENG Yun-hong, GAO Ru, LI Yan
    2019, 40 (1):  144-149.  DOI: 10.12068/j.issn.1005-3026.2019.01.027
    Abstract ( 558 )   HTML   PDF (617KB) ( 732 )  
    In order to study the impact of environmental regulation on inter-regional transfer decision making of polluting enterprises, the evolutionary game model was constructed in which the enterprises and local government were taken as the gaming subjects, and the evolutionary game replicator dynamic equation was used to simulate the decision-making process between the two subjects. The results showed that the main factors affecting decision choices of the government of target district are the tax expenditure sharing, the cost of default and additional transfer payments to the enterprises; the decision-making choices of polluting enterprises are mainly affected by the government′s reward income and the difference of environmental regulation expenditure between the original district and target district. When there are two kinds of incentives for the government of target district and polluting enterprises, the polluting enterprises will choose transfer strategies if the initial will of the two players can stimulate the government to further relax environmental regulation.
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    Mathematics
    Canal Surfaces in 3D Minkowski Space
    QIAN Jin-hua, FU Xue-shan
    2019, 40 (1):  150-152.  DOI: 10.12068/j.issn.1005-3026.2019.01.028
    Abstract ( 742 )   HTML   PDF (261KB) ( 811 )  
    The canal surfaces with time-like center curves in 3D Minkowski space were defined and the Weingarten canal surfaces were classified. Similar to the studying method for surfaces in Euclidean space, at first, the parametric equation of canal surfaces under pseudo orthogonal frame was built according to the Frenet frame of time-like curves and the geometric definition of canal surfaces, then the basic theories were obtained which include two fundamental quantities, the Gaussian curvature and mean curvature and so on. Using basic theories, the relationship between the Gaussian curvature and the mean curvature were found and the Weingarten canal surfaces were studied explicitly. The conclusion was achieved that a canal surface is a Weingarten surface if and only if it is a tube or a revolution surface.
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