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3rd International Conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2024

作者： Hu, Xinyu Han, Wei Cao, Xinnan Zhou, Jinfei Jiang, Wangjie State Grid Nantong Power Supply Company Nantong Jiangsu226000 China

ISBN: (纸本)9798331519032

In the process of distribution network planning (DNP), massive heterogeneous data, such as power system operation data, enterprise operation management data, nonelectric energy data, etc., bring challenges to data processing because of their high dimension, large volume and strong coupling. Aiming at these problems, this paper proposes a DNP method combining multi-source heterogeneous data (MHD) processing technology and optimization algorithm. This method fuses multi-source data by Kalman filter (KF) to improve data accuracy, and extracts key features by principal component analysis (PCA) to provide a simplified data set for subsequent optimization. In the aspect of optimization algorithm, the multi-objective optimization algorithm NSGA-II is used to solve the DNP problem, taking into account the objectives of economy and reliability, and satisfying the physical constraints such as power flow balance, voltage limitation and line capacity. The experimental results show that this method is superior to the traditional planning method in terms of total investment cost, operation cost, average power outage time and power supply reliability, which effectively verifies its effectiveness and superiority. The research in this paper provides new ideas and methods for intelligent DNP, which is helpful to improve the safety, stability and economic operation level of power system. © 2024 IEEE.

关键词： distribution network planning system Kalman filtering Multi-source heterogeneous data optimization algorithm principal component analysis

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Research on the Construction of Smart Grid Digital System Based on Big Data Cloud Computing Model optimization algorithm 4

Research on the Construction of Smart Grid Digital System Ba...

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4th IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2024

作者： Li, Zhipeng Liu, Shaobo Zhang, Jianfeng Wang, Jun Shen, Shuo State Grid Gansu Electric Power Company Lanzhou China State Grid Gansu Electric Power Company Digital Division Lanzhou China

ISBN: (纸本)9798350359589

An intelligent power business development method based on digital service information is proposed. At the same time, a complete data mining framework is constructed. Parameters such as distance of adjacent pixels, similarity degree of carrier components and average amplitude were determined by coding and parsing. Then the digital business information resources are extracted. The mining method of data cloud in power system based on time series is established. The correlation degree of each information characteristic of middle station is analyzed based on classification and characteristic identification of power system middle station. Experiments show that the algorithm can effectively improve the distribution of data in the middle station in every minute. The standard deviation of the algorithm is reduced and the mining effect is improved. © 2024 IEEE.

关键词： artificial intelligence digital system optimization algorithm smart grid

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optimization algorithm on the Intelligence Schedule of Pubic Traffic Vehicles

Optimization Algorithm on the Intelligence Schedule of Pubic...

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The 2011 International Conference on Electric and Electronics(EEIC 2011)

作者： Cui Yonghong Wang Qingrong School of Traffic and Transportation Engineering Lanzhou Jiaotong University School of Electronic and Information Engineering Lanzhou Jiaotong University

In this paper A model and the Genetic algorithm for intelligent schedule of public traffic vehicles is researched according to the characteristics of the public transportation vehicles' scheduling, It adopts the true value of the coding method using the start time as the variable and uses the penalty function method to add a variety of constraints to the objective function when constructing the fitness function, which simplified the calculation. Finally, the simulation results are obtained by using the improved Genetic algorithm for solving the non-uniform grid schedule, and a case study is carried out to verify the validity, objectivity and applicability of this model through calculated and analyzed practical data. Results show that the improved Genetic algorithm can find the approximate best result in the huge search space of optimization.

关键词： intelligent schedule optimization algorithm genetic algorithm fitness function

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Research on Pricing Decisions optimization algorithm of Fresh Agricultural Product Supply Chain Under the Background of Artificial Intelligence

Research on Pricing Decisions Optimization Algorithm of Fres...

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作者： Xu, Yunfei Wang, Xianjun Yu, Huaizhi Shandong Guonong Logistics Technology Co. Ltd. Jinan China Shandong Institute of Commerce and Technology Jinan China

With the economic development and the improvement of cold chain logistics service technology, more and more fresh food enterprises are committed to expanding their retail scope, seizing market share and improving their profits. This paper studies the pricing decision optimization algorithm of fresh agricultural product supply chain under the background of artificial intelligence, aiming to improve the efficiency and competitiveness of fresh agricultural product supply chain. Aiming at the difficulties and challenges in the pricing decision of fresh agricultural products supply chain, an optimization algorithm is proposed. The algorithm considers the impact of delivery time on the pricing and service decisions of fresh agricultural products, aims to improve the revenue of supply chain members, constructs a dual-channel game model, analyzes and evaluates multiple links in the fresh agricultural product supply chain, optimizes the pricing strategy, and provides appropriate management suggestions for the relevant decisions of fresh supply chain members. This paper discusses and analyzes the relevant theories and methods of pricing decision-making in the supply chain of fresh agricultural products, selects the actual fresh agricultural products market as the experimental platform, and verifies the effectiveness and feasibility of the algorithm through experiments. The results show that the pricing decision optimization algorithm of fresh agricultural products supply chain based on artificial intelligence technology has high accuracy and efficiency, which can provide useful help for the management and optimization of fresh agricultural product supply chain. The results of this study are of great significance for the management and optimization of fresh agricultural supply chain, and the algorithm can be further studied and applied in the future to improve the efficiency and competitiveness of fresh agricultural product supply chain. © The Author(s), under exclusive licens

关键词： Artificial intelligence Game theory Model building optimization algorithm Supply chain

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A Wideband Butterfly Antenna Based on Deep Learning Parameter optimization algorithm

A Wideband Butterfly Antenna Based on Deep Learning Paramete...

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2020 Cross Strait Radio Science and Wireless Technology Conference

作者： Wang, Nan Kong, Zhizhan Ren, Xiaolong Chen, Songbo Dai, Guang Han, Kenlong Chen, Xiaojian He, Miao Du, Hao State Grid Shaanxi Elect Power Res Inst Xian Shanxi Peoples R China State Grid Shaanxi Elect Power Corp Xian Shanxi Peoples R China State Grid Shaanxi Maintenance Co Xian Shanxi Peoples R China Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian Shanxi Peoples R China

ISBN: (纸本)9781728181813

A wideband butterfly antenna based on deep learning parameter optimization algorithm is proposed in this paper. Two neural networks are designed to model the mapping relationship of structure parameters to frequency response and frequency response to structure parameters respectively. The parameter optimization algorithm proposed consists of two stages: training NN1 and optimizing parameters using NN2. A wideband butterfly antenna is designed to verify the algorithm. The experiment shows that the structure parameter optimization algorithm proposed can quickly optimize the structure parameters of antenna with the best preformance and save a lot of manpower and time cost.

关键词： antenna deep learning optimization algorithm

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optimization algorithm under Relaxed Constraints for Sequencing Component Pick and Placement in PCB Assembly

Optimization Algorithm under Relaxed Constraints for Sequenc...

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第35届中国控制会议

作者： Haiming LIU Peng YUAN Yueming HU Weidong LIU School of Automation Science and Engineering South China University of Technology

ISBN: (纸本)9781509009107

Many optimization algorithms proposed for PCB assembly problem had a common problem that they introduced strong constraints, which made optimization performance deteriorate in practice. Focusing on component pick and placement sequencing problem for multi-head placement machine in PCB assembly, this paper discuss some strong constraints involved in related optimization problem and propose an algorithm under relaxed constraints for problem solving. Certain strong constraints were relaxed for the algorithm to expand solution space, making it possible to find better solutions. Under such relaxation, an optimization algorithm based on scatter search（SS） method was constructed to solve the component sequencing problem, and steps of algorithm are detailed in the paper. Numerical experiments were made to conduct an evaluation for the proposed algorithm, along with a comparison with two heuristic algorithms proposed in other literatures. The results show that the proposed algorithm has better performance in optimization results and can shorten PCB assembly time of the placement machine effectively.

关键词： PCB assembly optimization algorithm relaxed constraint scatter search

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optimization algorithm for Task Allocation with Multi-objectives in Collaborative Manufacturing Project

Optimization Algorithm for Task Allocation with Multi-object...

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The 2011 International Conference on Smart Materials and Nanotechnology in Engineering (ICSMCE2011)

作者： Xianjie Wu Jin-zhu Cao Modern Educational Technology Center Zhejiang Gongshang University College Of Computer And Information Engineering Zhejiang Gongshang University

In the collaborative manufacturing project, task allocation among cooperative enterprises directly impacts the competition ability of enterprises and the overall economic benefits of the projectAiming at this problem, a new algorithm is proposed to get the optimal combination of shortest project time, lowest cost and minimum number of selected cooperative enterprisesThe algorithm is evaluated with an example and the result shows that the optimization solution can be applied in the actual collaborative projects with good effect.

关键词： Collaborative manufacturing project Cooperative enterprises Task allocation optimization algorithm

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optimization algorithm for Home Energy Management System Based on Artificial Bee Colony in Smart Grid

Optimization Algorithm for Home Energy Management System Bas...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Yanyu Zhang Peng Zeng Chuanzhi Zang Key Lab. of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781479987313

To implement demand response in residential sector and facilitate the integration of renewable resources and plug-in electric vehicles in future smart grid, this paper proposes a framework of home energy management system (HEMS) and a optimization algorithm for it based on improved artificial bee colony. The algorithm schedules the operations of schedulable home appliances according to electricity price, forecasted outdoor temperature and renewable power output, and user preferences to minimize user's electricity cost. The effectiveness of the algorithm is verified by simulations, and the electricity cost can be reduced by 47.76%.

关键词： Smart grid Demand response Home energy management system Artificial bee colony optimization algorithm optimization algorithms Smart grids Demand-Responsive bee colonies Energy management systems Domestic architecture electricity costs Bee User preferences

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optimization algorithm for Deformation Analysis of the Simply-supported Beam

Optimization Algorithm for Deformation Analysis of the Simpl...

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2007国际机械工程与力学会议

作者： Xu ZHANG Changzheng CHEN Jie XU School of Mechanical and Electronic Engineering Tianjin Polytechnic University School of Mechanical Engineering Shenyang University of Technology School of Materials Science and Engineering University of Science and Technology Beijing

In this work, an optimization algorithm is presented for deformation analysis of the simply-supported beam. The principal feature of the optimization algorithm is that the equilibrium state with elastic-plastic deformation is chosen as the study object. The constitutive law adopts elastic-linearly strain-hardening plastic model and the shearing deformation is considered. The endpoint coordinates are given through coordinate recursion formulae, and an objective function is defined by unknown endpoint coordinates of slight segments. The optimization problem for deformation analysis of a simply-supported beam is established, and the optimization program is programmed. Typical examples are calculated by optimization algorithm, and the results are in very good agreement with those by finite element method.

关键词： Nonlinear analysis Elastic-linearly strain-hardening plastic model Shearing deformation Finite element method optimization algorithm

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optimization algorithm in the Simulation of Ceramic Grain Growth

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厦门大学学报（自然科学版） 2002年第S1期41卷 292-页

作者： ZENG Zhong-chen 1, JI Guo-li 1, XIONG Zhao-xian 2, LIU Zong-xi 1 (1. Department of Automation, Xiamen University, 2. Department of Materials Science and Engineering, Xiamen University, Xiamen 361005, China)

optimization algorithm was developed for the simula ti on of ceramic grain growth at atomistic scale. Based on the coordination informa tion of different atoms, a structure of trident tree was applied to save large q uantities data, so as to solve the problems of large data information and long r unning time. For every atom a binary tree was firstly formed according to the X coordination of atom. If the values of X coordination were the same, the middle sub-tree of first layer formed then a binary tree according to the Y coordinati on of atom. If the values of Y coordination were also the same, the middle sub- tree of second layer formed then a binary tree according to the Z coordination o f atom. In this way the speed of whole program is enhanced obviously. In order t o reduce memory, in this structure only need to store the exterior atoms’ infor mation, an integer is used to store the interior atoms’ information. If other a toms take up an atom’s all adjacent positions, this atom will be deleted in the data structure, for all the adjacent positions’ atoms, the integer’s relative bit will be set 1 to denote that there is an atom in this position but not be s tored in the trident tree. When an outside atom is deleted, for all the bits tha t are set 1,an atom will be added to the trident tree as an outside atom for the relative positions. And for this new added atom, the integer’s relative bi t of all the adjacent position’s atoms should be set 0 to denote that there is no interior atom in this position. In this way, if there are n 3 atoms, onl y need to store 6n 2 quantity’s atoms’ information. Large quantity of mem ory space can then be saved.

关键词： optimization algorithm computer simulation cera mic grain growth

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