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Fertilizer Strength Prediction Model Based on Shape Characteristics

IEEE ACCESS 2021年 9卷 87007-87023页

作者： Zhang, Hongjian Xu, Chunbao Wang, Jinxing Shandong Agr Univ Coll Mech & Elect Engn Tai An 271018 Shandong Peoples R China Shandong Prov Key Lab Hort Machinery & Equipment Tai An 271018 Shandong Peoples R China Shandong Agr Equipment Intelligent Engn Lab Tai An 271018 Shandong Peoples R China

The accurate prediction of fertilizer strength can reduce the crushing rate in the process of transportation and utilization, ensure the efficient utilization of fertilizer, so as to realize the sustainable and clean production of crops. To achieve this goal, for the first time, a fertilizer strength prediction model based on the shape characteristics is proposed to this paper by the support vector machine and the improved differential evolution algorithm. Firstly, the fertilizer shape characteristics and strength are measured by the independently developed agricultural material shape analyzer and the digital strength tester. Secondly, a fertilizer strength prediction model based on a support vector machine is constructed, in which the optimal combined kernel function is proposed according to the Pearson correlation coefficient and the normal distribution law. Finally, a differential evolution algorithm is improved to optimize the internal parameters of the fertilizer strength prediction model. The experiment results show that the maximum error rate of the fertilizer strength prediction model is between -5% and 5%. The proposed method of this paper can lay a solid foundation for fertilizer production and quality inspection, which will help reduce fertilizer crushing, improve fertilizer utilization to realize the sustainable and clean production of crops.

关键词： Fertilizers Shape Shape measurement Predictive models Particle measurements Atmospheric measurements Pollution measurement Fertilizer strength prediction model shape characteristics support vector machine combined kernel function improved differential evolution algorithm

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A disjunctive belief rule-based expert system for bridge risk assessment with dynamic parameter optimization model

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 113卷 459-474页

作者： Yang, Long-Hao Wang, Ying-Ming Chang, Lei-Lei Fu, Yang-Geng Fuzhou Univ Decis Sci Inst Fuzhou 350116 Fujian Peoples R China Xian High Tech Inst Dept Management Xian 710025 Shaanxi Peoples R China Fuzhou Univ Sch Math & Comp Sci Fuzhou 350116 Fujian Peoples R China

Bridge risk assessment is an important approach to avoiding the safety accidents of bridges and ensuring the safety of the public. This can be done by investigating the relationship between bridge risks and bridge criteria. However, such relationship usually is highly complicated in actual situations. In this regard, many approaches were proposed to model bridge risks in the past decades. Particularly, four alternative approaches including the artificial neural network (ANN), evidential reasoning with learning (ERL), multiple regression analysis (MRA), and adaptive neuro-fuzzy inference system (ANFIS) were deeply analyzed and compared for bridge risk assessment. However, these approaches are restricted by their shortages. Thus, this paper utilizes the disjunctive belief rule-based (DBRB) expert system to model bridge risks, where the DBRB expert system is one type of the belief rule-based (BRB) expert system by considering disjunctive belief rules (DBRs) rather than conjunctive belief rules (CBRs) in a BRB. Furthermore, the dynamic parameter optimization model and improved differential evolution (IDE) algorithm are proposed to train the parameters of the DBRB expert system, where the model is applied to ensure the completeness of a DBRB and the algorithm is used to get the global optimal solution. For justification purpose, two existing parameter optimization models and nine alternative models developed by the ANN, ERL, MRA, and ANFIS are applied to assess bridge structures. Comparison results indicate that the DBRB expert system with the dynamic parameter optimization model is better than those alternative models and existing parameter optimization models.

关键词： Bridge risk assessment Disjunctive belief rule-based expert system Dynamic parameter optimization model improved differential evolution algorithm Completeness

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A New Fuzzy Sliding Mode Control Method for Permanent Magnet Synchronous Motor Servo System Based on Optimization of Fuzzy Rules

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IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2022年第12期17卷 1748-1754页

作者： Guo, Liang Zhang, Xu Zheng, Chao Zhang, Peng Wu, Xiaowen Zhejiang Sci Tech Univ Fac Mech Engn & Automat Hangzhou 310018 Peoples R China Zhejiang Fangyuan Test Grp Co Ltd Hangzhou 310018 Peoples R China

Aiming at the problems of inherent chattering of traditional sliding mode control system of permanent magnet synchronous motor and further improving the control precision, a new fuzzy exponential reaching law sliding mode control method optimized by improved differential evolution (DE) algorithm (DEFSMC) is proposed in this article. A new hyperbolic tangent function with fuzzy boundary layer is proposed to instead of the traditional switching function, and the improved DE algorithm is used to optimize the fuzzy rules of parameters in sliding mode controller. Simulation and experimental results prove that the proposed strategy can effectively reduce the chattering and overshoot, and improve the response speed and robustness of the system. (c) 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

关键词： fuzzy sliding mode control fuzzy hyperbolic tangent function improved differential evolution algorithm

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Application of machine learning and its improvement technology in modeling of total energy consumption of air conditioning water system

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第5期19卷 4841-4855页

作者： Zhu, Qixin Liu, Mengyuan Liu, Hongli Zhu, Yonghong Suzhou Univ Sci & Technol Sch Mech Engn 55 Changjiang Rd Suzhou 215009 Peoples R China Suzhou Univ Sci & Technol Jiangsu Prov Key Lab Intelligent Bldg Energy Effi 1 Kerui Rd Suzhou 215009 Peoples R China Suzhou Univ Sci & Technol Sch Environm Sci & Engn 1 Kerui Rd Suzhou 215009 Peoples R China Jingdezhen Ceram Inst Sch Mech & Elect Engn Sch Mech Engn 27 Taoyang South Rd Jingdezhen 333001 Peoples R China

Accurate energy consumption model is the basis of energy saving optimal control of air conditioning system. The existing energy consumption model of air conditioning water system mainly focuses on a certain equipment or a part of the cycle. However, the coupling between water system equipment will affect the setting of optimal energy consumption of equipment. It is necessary to establish the energy consumption model of water system as a whole. However, air conditioning water system is a highly nonlinear complex system, and its precise physical model is difficult to establish. The main goal of this paper is to develop an accurate machine learning modeling and optimization technique to predict the total energy consumption of air conditioning water system by using the actual operation data collected. The main contributions of this work are as follows: (1) Three commonly used machine learning techniques, artificial neural network (ANN), support vector machine (SVM) and classification regression tree (CART), are used to build prediction models of air conditioning water system energy consumption. The results show that all the three models have fast training speed, but the ANN model has better performance in cross-validation. (2) The improved differential evolution algorithm was used to optimize the parameters (initial weights and thresholds) of the ANN, which solved the problem that the ANN is easy to fall into the local optimal solution. The simulation results show that the root mean square error (RMSE) of the improved model decreases by 20.5%, the mean absolute error (MAE) decreases by 30.2%, and the coefficient of determination (R2) increases from 0.9227 to 0.9512. (3) Sensitivity analysis of the established optimization model shows that chilled water flow, chilled water outlet temperature and air conditioning load are the main factors affecting the total energy consumption.

关键词： machine learning data-driven model artificial neural network support vector machine improved differential evolution algorithm

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An adaptive differential evolution algorithm based on relaxation strategy to realize the Nash equilibrium of multi-oligopoly game

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QUAESTIONES MATHEMATICAE 2024年第8期47卷 1571-1587页

作者： Li, Huimin Xiang, Shuwen Huang, Shiguo Luo, Enquan Xuzhou Univ Technol Sch Math & Stat Xuzhou 221018 Peoples R China Guizhou Univ Coll Math & Stat Guiyang 550025 Peoples R China Guiyang Univ Coll Math & Informat Sci Guiyang 550005 Peoples R China Zhengzhou Univ Light Ind Dept Math & Informat Sci Zhengzhou 450002 Peoples R China Guizhou Univ Acad Affairs Off Guiyang 550025 Peoples R China

Inspired by the idea of game learning, this paper studies the Cournot game model of the multi-oligopoly market and studies the realization of the Nash equilibrium by using adaptive differential evolution algorithm based on relaxation strategies. The realization path of Nash equilibrium is attained through an adaptive differential evolution based on a relaxation strategy procedure applied to an objective function with best response dynamics. Among them, the objective function is derived from the sum of the payoff changes of each oligopoly under best response decisions. And theoretically proved that the Nash equilibrium is the optimal solution of the objective function.

关键词： Multi-oligopoly game Nash equilibrium best response dynamics bounded rationality improved differential evolution algorithm

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Energy-aware Resource Allocation Scheme for Device-to-Device Communication Based on NOMA Underlaying Cellular Networks 17

Energy-aware Resource Allocation Scheme for Device-to-Device...

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IEEE 17th International Conference on Communication Technology (ICCT)

作者： Li, Bingshan Zhang, Heli Ji, Hong Li, Xi Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing Peoples R China

ISBN: (纸本)9781509039449

In this paper, power-domain NOMA is applied to D2D communications, and then an optimization problem to maximize the system total energy efficiency (EE) is formulated while guarantying the quality of service (QoS) of both cellular users and D2D users. This optimization problem is a mixed integer fractional programming (MIFP) with a large-scale solution space. Then in order to solve the problem with low complexity, a novel energy aware resource allocation scheme based on improved differential evolution algorithm (EARASIDE) is developed. It is a joint physical resource block (RB) allocation and power control scheme. Finally, extensive simulation results show that the proposed EARAS-IDE algorithm with a low complexity is able to converge quickly and approximate the optimal solution after introducing the dynamic mutation factor F. Additionally, compared with OMA scheme, the NOMA scheme achieves higher EE performance gains at the cost of slightly increased receiver complexity.

关键词： D2D communication NOMA energy efficiency quality of service improved differential evolution algorithm

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Research on algorithm and Project Application for Distribution Automation Optimization Planning

Research on Algorithm and Project Application for Distributi...

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International Conference on Sustainable Power Generation and Supply

作者： Zhao Lihua Xu Lizhong Xiao Xianjian Ding Xiaofeng Liu Jun Hohai Univ Nanjing 210098 Peoples R China

ISBN: (纸本)9781424449347

The paper analyzes the character of distribution network, utilizes the multi-objective differential evolution algorithm to carry on selecting and location optimization about the automatic equipment, takes switch as code of the chromosome gene, in each evolutionary generation, divides the community into three sub-communities which execute variation, crossover, fitness evaluation and select operation based on three factors respectively: Energy not supply (ENS), communication optical fiber cost, automation device invests. Then combine best individual into one unit, performances evolution operation on the next generation. By iterate process to obtain the best network scheme of distribution network automation planning finally. This paper analyzed the fault mode and consequence analytic method (FMEA) in the project usability, and made an improvement for this method, it means according to actual transmission capacity limit of the circuit, carry on verification of the load transfers through the flow calculation. As an auxiliary derision support system, the paper adopts visualization technology of based on the AUTOCAD, demonstrates the plan result on the geography background map, finally introduces the real distribution network application as an example.

关键词： distribution network improved differential evolution algorithm artificial intelligence auxiliary decision support system

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Joint inversion of VES and Rayleigh wave data based on improved DE algorithm for near surface exploration

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WORLD JOURNAL OF ENGINEERING 2024年第2期21卷 242-253页

作者： Hu, Benna Wen, Laifu Zhou, Xuemei Hebei Inst Invest & Design Water Conservancy & Hyd Geol Survey Inst Tianjin Peoples R China Hebei Univ Engn Sch Earth Sci & Engn Handan Peoples R China Hebei Univ Engn Acad Journal Editorial Off Handan Peoples R China

PurposeVertical electrical sounding (VES) and Rayleigh wave exploration are widely used in the exploration of near-surface structure, but both have limitations. This study aims to make full use of the advantages of the two methods, reduce the multiple solutions of single inversion and improve the accuracy of the inversion. Thus, a nonlinear joint inversion method of VES and Rayleigh wave exploration based on improved differential evolution (DE) algorithm was proposed. Design/methodology/approachBased on the DE algorithm, a new initialization strategy was proposed. Then, taking AK-type with high-velocity interlayer model and HA-type with low-velocity interlayer model near the surface as examples, the inversion results of different methods were compared and analyzed. Then, the proposed method was applied to the field data in Chengde, Hebei Province, China. The stratum structure was accurately depicted and verified by drilling. FindingsThe synthetic data and field data results showed that the joint inversion of VES and Rayleigh wave data based on the improved DE algorithm can effectively improve the interpretation accuracy of the single-method inversion and had strong stability and large generalizable ability in near-surface engineering problems. Originality/valueA joint inversion method of VES and Rayleigh wave data based on improved DE algorithm is proposed, which can improve the accuracy of single-method inversion.

关键词： Vertical electrical sounding Rayleigh wave exploration Near-surface exploration improved differential evolution algorithm Nonlinear joint inversion

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Effects of land use changes on the ecological operation of the Panjiakou-Daheiting Reservoir system, China

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ECOLOGICAL ENGINEERING 2020年 152卷 105851-105851页

作者： Miao, Yuanjingjing Li, Jianzhu Feng, Ping Dong, Lixin Zhang, Ting Wu, Jiezhao Katwal, Rajeev Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300350 Peoples R China Tianjin Hydraul Res Inst Tianjin 300061 Peoples R China

The problem of insufficient water for ecological purposes in the Luanhe River basin requires urgent resolution. The regional hydrological cycle is affected by the Panjiakou-Daheiting Reservoir system and by changes in land use in the upper watershed. Therefore, this system was selected as a study area to simulate ecological reservoir operation and analyze the effects of changes in land use on ecological operation. A physical habitat simulation model (PHABSIM) was built to determine the minimum and suitable ecological water demand. Then, an ecological reservoir operation model using an improved differential evolution (DE) algorithm was established. Simulated inflow data under the land use conditions in 1970 and 2015 were input into the model, and the effects of changes in land use on ecological operation and on the weighted usable area (WUA) for cyprinoids were calculated. The results show that ecological reservoir operation significantly improves the ecological water supply and increases cyprinoid habitat. The changes in land use led to a decrease in annual runoff, which further reduced the urban water supply by 0.67%-2.25% and the ecological water supply by 0.45%-2.04% at different flow frequencies. The land use changes also caused the WUA to decrease by 1746-2999 m(2)/km at different flow frequencies, with a decrease rate of 1.04%-6.28%. This study could provide valuable information for water resource managers operating reservoirs in river ecosystems and planning to cope with water shortages caused by land use change in water-deficient areas.

关键词： improved differential evolution algorithm PHABSIM model Ecological reservoir operation Land use changes Ecological water demand

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Piezoelectric-based smart structures for aero-engine blade: Piezoelectric layout optimization and vibration suppression tests

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AEROSPACE SCIENCE AND TECHNOLOGY 2024年 153卷

作者： Gao, Zhiyuan Xu, Tongxin Yu, Ruichen Jiang, Jinhua Zhu, Xiaojin Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200444 Peoples R China

To promote the use of piezoelectric smart structures in aero-engine blades, this paper introduces a novel method for optimizing the layout of piezoelectric elements on the blade's surface and an active vibration control method, along with vibration suppression tests. A preprocessing method is introduced for the point cloud data of inservice blades to reconstruct the blade surface. An improved parameter-adaptive differential evolution algorithm is proposed to optimize the layout of piezoelectric actuators and sensors and accurately identify the hysteresis nonlinear model of piezoelectric elements. A Hammerstein model is constructed by cascading an asymmetric Bouc-Wen model with an ARX model to describe the rate-dependent hysteresis nonlinear characteristics of piezoelectric elements. An improved variable step-size FxLMS algorithm is proposed to balance the relationship between convergence speed and steady-state error in the control algorithm. The proposed layout optimization and vibration control algorithm are validated experimentally on an experimental platform under various disturbances, with results showing improved performance of the proposed VSS-FxLMS algorithm in terms of convergence and efficiency.

关键词： Piezoelectric smart structures Surface reconstruction Layout optimization improved differential evolution algorithm Hammerstein model Active vibration control

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