检索结果-南通市图书馆

Performance evaluation for intelligent optimization algorithms in self-potential data inversion

在线全文

学校读者我要写书评

暂无评论

Journal of Central South University 2016年第10期23卷 2659-2668页

作者：崔益安朱肖雄陈志学刘嘉文柳建新 School of Geosciences and Info-Physics Central South University Changsha 410083 China Hunan Key Laboratory of Nonferrous Resources and Geological Hazard Detection (Central South University) Changsha 410083 China Key Laboratory of Metallogenic Prediction of Nonferrous Metals Ministry of Education (Central South University) Changsha 410083 China

The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and efficiently: simulated annealing, genetic, particle swarm optimization, and ant colony optimization. Using both noise-free and noise-added synthetic data, it is demonstrated that all four intelligent algorithms can perform self-potential data inversion effectively. During the numerical experiments, the model distribution in search space, the relative errors of model parameters, and the elapsed time are recorded to evaluate the performance of the inversion. The results indicate that all the intelligent algorithms have good precision and tolerance to noise. Particle swarm optimization has the fastest convergence during iteration because of its good balanced searching capability between global and local minimisation.

关键词： self-potential inversion intelligent algorithm

Research on tasks schedule and data transmission of video sensor networks based on intelligent agents and intelligent algorithms

在线全文

学校读者我要写书评

暂无评论

The Journal of China Universities of Posts and Telecommunications 2009年第6期16卷 84-91,112页

作者： HUANG Hai-ping WANG Ru-chuan SUN Li-juan WANG Hai-yuan XIAO Fu College of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China

As a novel application technology,wireless video sensor networks become the current research focus,especially on target tracking and surveillance scenario.Based on multiple agents＇ technique,this article introduces a series of intelligent algorithms such as simulated annealing algorithm（SA）,genetic algorithm（GA）,and ant colony optimization algorithm（ACO） or their mixed algorithms,to resolve the optimization of tasks schedule and data transmission.This article analyzes the performance of abovementioned algorithms and verifies their feasibility associated with agents.The simulations demonstrates that the mixed algorithms based on SA and GA obtain the optimal solution to tasks schedule,and those combined with SA-ACO show advantages on multimedia sensor networks routing optimization.

关键词： video sensor networks intelligent algorithm tasks schedule optimal routing agent

Modelling and reviewing the reliability and multi-objective optimization of wind-turbine system and photovoltaic panel with intelligent algorithms

在线全文

学校读者我要写书评

暂无评论

Clean Energy 2021年第4期5卷 713-730页

作者： Reza Alayi Mehdi Jahangiri John William Grimaldo Guerrero Ravil Akhmadeev Rustem Adamovich Shichiyakh Sara Abbasi Zanghaneh Department of Mechanics Germi BranchIslamic Azad UniversityGermiIran Department of Mechanical Engineering Shahrekord BranchIslamic Azad UniversityShahrekordIran Departamento de Energía Universidad de la CostaBarranquillaColombia Plekhanov Russian University of Economics Stremyanny lane36Moscow117997Russian Federation Department of Management Candidate of Economic SciencesKuban State Agrarian University named after I.T.TrubilinKrasnodarRussian Federation Department of Energy Engineering Energy Institute of Higher EducationSavehIran

One of the options for non-dependence on fossil fuels is the use of renewable energy,which has not grown significantly due to the variable nature of this type of energy.The combined use of wind and solar energy as energy sources can be a good solution to the problem of variable energy output.Therefore,the purpose of this research is to model a combination of the wind-turbine system and photovoltaic cell,which is needed to investigate their ability to supply electrical energy.To determine this important power production,real data of solar-radiation intensity and wind are used and,in modelling photovoltaic cells,the effects of ambient temperature are also considered.In order to generalize the studied system in all dimensions,different scenarios have been considered.According to the amount of electrical power generated,during the evaluation of these scenarios,two economic parameters,namely the selected scenario of a wind/solar system with diesel-generator support,was determined.

关键词： reliability wind turbine photovoltaic cell intelligent algorithm economic analysis

A Reliability Evaluation Method for Intermittent Jointed Rock Slope Based on Evolutionary Support Vector Machine

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2021年第10期129卷 149-166页

作者： Shuai Zheng An-Nan Jiang Kai-Shuai Feng College of Transportation Engineering Dalian Maritime UniversityDalian116026China

The randomness of rock joint development is an important factor in the uncertainty of geotechnical engineering stability.In this study,a method is proposed to evaluate the reliability of intermittent jointed rock slope.The least squares support vector machine(LSSVM)evolved by a bacterial foraging optimization algorithm(BFOA)is used to establish a response surface model to express the mapping relationship between the intermittent joint parameters and the slope safety factor.The training samples are obtained from the numerical calculation based on the joint finite element method during this process.Considering the randomness of the intermittent joint parameters in the actual project,each parameter is evaluated at different locations on the site,and its distribution characteristics are counted.According to these statistical results,a large number of parameter combinations are obtained through Monte Carlo sampling.The trained machine learning mapping model is used to obtain the slope safety factor corresponding to each group,and these results are then used to obtain the slope reliability.When the research results were applied to slope disaster treatment along the Yalu River in China’s Jilin Province,it was found that the joint length and joint inclination angle both play key roles in rock slope stability,which should receive more attention in the slope treatment.In summary,this study establishes a method for evaluating the reliability of intermittent jointed rock slope based on an evolutionary SVM model,and its feasibility is verified by engineering application.

关键词： Slope reliability intermittent joint safety factor intelligent algorithm parameter sensitivity

Particle Swarm Optimization Based on Hybrid Kalman Filter and Particle Filter

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Shanghai Jiaotong university(Science) 2020年第6期25卷 681-688页

作者：彭湃陈聪杨永胜 School of Aeronautics and Astronautics Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Integrated Technology of Avionics System Shanghai 201103China

The combination of particle swarm and filters is a hot topic in the research of particle swarm op-timization(PSO).The Kalman filter based PSO(K-PSO)algorithm is efficient,but it is prone to premature convergence.In this paper,a particle filter based PSO(P-PSO)algorithm is proposed,which is a fine search with fewer premat ure problems.Unfortunately,the P-PSO algorithm is of higher computational complexity.In order to avoid the premature problem and reduce the computational burden,a hybrid Kalman filter and particle filter based particle swarm optimization(HKP-PSO)algorithm is proposed.The HKP-PSO algorithm combines the fast convergence feature of K-PSO and the consistent convergence performance of P-PSO to avoid premature convergence as well as high computational complexity.The simulation results demonstrate that the proposed HKP-PSO algorithm can achieve better optimal solution than other six PSO related algorithms.

关键词： particleswarm opt imization(PSO) Kalman filter particle filter intelligent algorithm

Accurate Torque Modeling With PSO-Based Recursive Robust LSSVR for a Segmented-Rotor Switched Reluctance Motor

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

CES Transactions on Electrical Machines and Systems 2020年第2期4卷 96-104页

作者： Jiangling Wu Xiaodong Sun Jianguo Zhu Automotive Engineering Research Institute Jiangsu UniversityZhenjiang 212013China School of Electrical and Information Engineering University of SydneyNSW 2006Australia

In order to improve the reliability in torque calculation of SRM,an accurate nonlinear torque model regresses by recursive robust least squares support vector regression(RR-LSSVR)is proposed in this paper.The model is in terms of a segmented-rotor switched reluctance motor(SSRM).The characteristics of the SSRM is introduced to show its nonlinear characteristics both in magnetic and torque.Then,its mathematic model is established,and an accurate inductance measurement method and a torque calculation method are presented.After this,the principle of the RR-LSSVR and why it can adjust weights according to errors are described.The model used the RR-LSSVR algorithm shows an outstanding capability in accuracy and quickness compared with other algorithms.Finally,to further validate the accuracy of the proposed model in practical application,simulation and experiment are designed based on a 16/10 SSRM.

关键词： Switched reluctance motor intelligent algorithm nonlinear modeling torque calculation LSSVR

Business Plan for Autonomous Delivery Robot

在线全文

学校读者我要写书评

暂无评论

intelligent Control and Automation 2020年第2期11卷 33-46页

作者： Yangyang Li Kansas State University Manhattan KS USA

This paper introduces an autonomous robot (AR) cart to execute the last mile delivery task. We use navigation and intelligent avoidance algorithms to plan the path of the automatic robot. When AR encounters a new unrecognizable terrain, it will give control to the customer who can control the AR on its mobile app and navigate to the specified destination. We have initially designed an autonomous delivery robot with the cost of 2774 dollars.

关键词： Autonomous Robot Online Order Delivery Within-Community intelligent algorithm

An improved differential evolution algorithm for artificial neural networks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An improved differential evolution algorithm for artificial ...

Comparative Study on Several PSO algorithms

第30届中国控制与决策会议

作者： Wei Li Lei Yu School of Computer Science and Engineering Xi’an University of Technology

DE, which is a well-known intelligence optimization algorithm, has been widely used in solving science and engineering problems. However, the search performance of DE algorithm depends on control parameter settings. It is possible that poor settings for the parameters may cause the population to move towards undesirable values. In order to improve the performance of DE, this paper proposed an improved optimization algorithm based on JADE（MJADE）. In MJADE, the number of best individuals selected from the current population is dynamically adjusted to keep a balance between exploration and exploitation. Moreover, a modified mutation operation is designed. To verify the effectiveness of MJADE, numerical experiments are carried on ten benchmark problems from CEC2014. In addition, an application problem of artificial neural network is examined. The experimental results show that MJADE is competitive with respect to other compared algorithms in this simulation example.

关键词： intelligent algorithm Differential evolution Modified JADE Global optimization Neural network

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Comparative Study on Several PSO Algorithms