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32nd Chinese Control And Decision Conference (CCDC)

作者： Li, Xue-Long Wang, Jie-sheng Yang, Xue Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114044 Peoples R China

ISBN: (纸本)9781728158556

invasive weed optimization (IWO) algorithm a kind of stochastic optimization algorithm to simulate the weeds propagation phenomena based on the characteristics of weeds and the swarm behavior of plants in nature. The classical IWO algorithm has the problem that it is easy to fall into the local optimum, which will lead to the low precision. An new improved IWO algorithm based on the differential evolution operators was proposed to solve the one-dimensional bin packing (BP) problem. The proposed differential evolution invasive weed optimization (DE-IWO) algorithm, the genetic algorithm (GA), the firefly algorithm (FA) and the IWO algorithm are used to solve the three bin packing problems with different sizes. The simulation results verify the effectiveness of the proposed algorithm.

关键词： invasive weed optimization algorithm Differential Evolution Bin Packing Problem

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invasive weed optimization algorithm Based on Differential Evolution Operators to Solve Bin Packing Problem

Invasive Weed Optimization Algorithm Based on Differential E...

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第32届中国控制与决策会议

作者： Xue-Long Li Jie-sheng Wang Xue Yang School of Electronic and Information Engineering University of Science & Technology Liaoning

invasive weed optimization(IWO) algorithm a kind of stochastic optimization algorithm to simulate the weeds propagation phenomena based on the characteristics of weeds and the swarm behavior of plants in *** classical IWO algorithm has the problem that it is easy to fall into the local optimum,which will lead to the low *** new improved IWO algorithm based on the differential evolution operators was proposed to solve the one-dimensional bin packing(BP) *** proposed differential evolution invasive weed optimization(DE-IWO) algorithm,the genetic algorithm(GA),the firefly algorithm(FA) and the IWO algorithm are used to solve the three bin packing problems with different *** simulation results verify the effectiveness of the proposed algorithm.

关键词： invasive weed optimization algorithm Differential Evolution Bin Packing Problem

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Application of invasive weed optimization algorithm to Optimally Design Multi-Staged PID Controller for LFC Analysis

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INTERNATIONAL JOURNAL OF RENEWABLE ENERGY RESEARCH 2019年第1期9卷 470-479页

作者： Patel, Nimai Charan Debnath, Manoj Kumar Sahu, Binod Kumar Dash, Subhransu Sekhar Bayindir, Ramazan Govt Coll Engn Dept Elect Engn Keonjhar 758002 Odisha India Siksha O Anusandhan Univ Dept Elect Engn Bhubaneswar 751030 Odisha India Gazi Univ Fac Technol Dept Elect & Elect Engn Ankara Turkey

This article presents the study of frequency regulation of a solar energy based two area integrated power system equipped with multi-staged PID & conventional PID controller. To optimize the parameters of the projected multi-staged PID controllers, invasive weed optimization algorithm (IWOA) is employed. A disturbance to the extent of 0.01 p.u. is injected to the control area 1 to examine the effectiveness of the controllers in maintaining the system stability. Comparison of the results with respect to the magnitude of oscillations and settling time indicates that the proposed multi-staged PID controller outperforms the classical PID controller. The projected multi-staged PID controller optimised by the aforesaid algorithm (IWOA) helps in attaining nominal values of the tie-line power & frequency deviations during large parametric variation of the system and variation of system condition. Robustness of the proposed control strategy is established under various conditions such as (i) inclusion of a time delay of 0.7 s in each control area, (ii) wide variations of the system parameters and (iii) application of a random loading pattern in area 1.

关键词： Load frequency control invasive weed optimization algorithm thermal-solar power system multi-staged PID controller

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Multi-Staged PID Controller Tuned by invasive weed optimization algorithm for LFC Issues 7

Multi-Staged PID Controller Tuned by Invasive Weed Optimizat...

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7th International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Patel, Nimai Charan Debnath, Manoj Kumar Sahu, Binod Kumar Dash, Subhransu Sekhar Bayindir, Ramazan Govt Coll Engn Dept Elect Engn Keonjhar Odisha India Siksha O Anusandhan Univ Dept Elect Engn Bhubaneswar Odisha India Gazi Univ Fac Technol Dept Elect & Elect Engn Ankara Turkey

ISBN: (纸本)9781538659823

The article deals with the regulation of frequency comprising of interconnected dual area solar thermal system by employing PID and multi staged PID controller as secondary controller. A recently invented evolutionary algorithm called invasive weed optimization algorithm (IWOA) technique is used to tune the constraints of recommended controllers. To verify the supremacy of the controller a disturbance of 0.01 p.u. in control area-1 and a time delay of 0.7sec was introduced in both the areas. Investigation suggests that multi staged PID controller performs better in terms of settling time and magnitude of oscillation as compared to traditional PID controller. IWOA optimized multi staged PID controller attain the nominal values during large alteration in system condition and parameters.

关键词： Load Frequency Control invasive weed optimization algorithm Multi-staged PID controller Solar system

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Cognitive Radio Spectrum Assignment Based on invasive weed optimization algorithm

Cognitive Radio Spectrum Assignment Based on Invasive Weed O...

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2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)

作者： Wu Xie Xiao Li Chuanji Zhu Liangjie Yang Information and Communication Engineering College Harbin Engineering University Beijing Asimco Tianwei Oil Pump Oil Nozzle Co.LTD

According to the problem of the optimization of overall performance of idle spectrum assignment for cognitive radio, it proposed a spectrum assignment method for cognitive radio based on binary weed algorithm. Considering maximizing total network efficiency and fair effectiveness as a criterion, the algorithm is designed and implementation steps are presented. Simulation and analysis compares the solution of the spectrum assignment with Genetic algorithm and particle swarm algorithm. The results show that the spectrum assignment algorithm based on binary invasive weed algorithm has a higher performance. It can achieve maximizing sum reward and proportional fair better and receiving a better optimal solution.

关键词： cognitive radio spectrum assignment invasive weed optimization algorithm graph coloring

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Optimal Resource Planning of Smart Home Energy System under Dynamic Pricing Based on invasive weed optimization algorithm

Optimal Resource Planning of Smart Home Energy System under ...

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Smart Grids Conference (SGC)

作者： Lorestani, Alireza Ardehali, M. M. Gharehpetian, Gevork B. Amirkabir Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781509049882

This study deals with optimal resources planning of energy resources in smart home energy system (SHES), where PV (Photovoltaic) panel, battery and electrical heater (EH) are employed to meet all electrical and thermal demands. The advantage of this configuration is avoiding the use of two different energy carriers including electricity and natural gas in downstream users, in addition, reduction of SHES operation cost. An energy management controller (EMC) based on invasive weed optimization (IWO) algorithm is designed in order to optimize the energy routing and scheduling of different resources to obtain an efficient look-up table, by which the power generation of each energy resource is determined for all hourly time intervals. Different electricity tariffs and all operational constraints of energy resources are considered. Several scenarios are defined and the impacts of system components on SHES operation cost are investigated. Moreover, feasibility study of the proposed SHES based on different electricity and gas prices is conducted. It is observed that the proposed optimal scheduling based on IWO algorithm outperforms other approaches. Furthermore, it is shown that self-discharge rate of the battery, affects the system operational performance, especially time of charging and discharging of the battery.

关键词： Smart home energy management controller invasive weed optimization algorithm electrical heater

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EXPERIMENTAL VERIFICATION OF APPROXIMATE SOLUTION OF THE INVERSE STEFAN PROBLEM OBTAINED BY APPLYING THE invasive weed optimization algorithm

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THERMAL SCIENCE 2015年第Sup1期19卷 S205-S212页

作者： Hetmaniok, Edyta Slota, Damian Zielonka, Adam Silesian Tech Univ Inst Math Gliwice Poland

The paper proposes a procedure for solving the inverse Stefan problem consisted in reconstruction of the function describing the heat transfer coefficient on the basis of temperature measurements. Elaborated method is based on two procedures: solution of the appropriate direct Stefan problem by using the finite difference method combined with the alternating phase truncation method and minimization of some functional with the aid of invasive weed optimization algorithm. For verifying the effectiveness of investigated algorithm the experimental data obtained in the solidification of aluminum are used.

关键词： artificial intelligence evolutionary algorithms invasive weed optimization algorithm inverse Stefan problem

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invasive weed optimization algorithm for Optimizating the Parameters of Mixed Kernel Twin Support Vector Machines

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JOURNAL OF COMPUTERS 2013年第8期8卷 2077-2084页

作者： Huang, Huajuan Ding, Shifei Zhu, Hong Xu, Xinzheng China Univ Min & Technol Sch Comp Sci & Technol Xuzhou 221116 Peoples R China Chinese Acad Sci Inst Comp Technol Key Lab Intelligent Informat Proc Beijing 100190 Peoples R China

How to select the suitable parameters and kernel model is a very important problem for Twin Support Vector Machines (TSVMs). In order to solve this problem, one solving algorithm called invasive weed optimization algorithm for Optimizating the Parameters of Mixed Kernel Twin Support Vector Machines (IWO-MKTSVMs) is proposed in this paper. Firstly, introducing the mixed kernel, the twin support vector machines based on mixed kernel is constructed. This strategy is a good way to solve the kernel model selection. In order to solve the parameters selection problem which contain TSVMs parameters and mixed kernel model parameters, invasive weed optimization algorithm (IWO) is introduced. IWO is an optimization algorithm who has strong robustness and good global searching ability. Finally, compared with the classical TSVMs, the experimental results show that IWO-MKTSVMs have higher classification accuracy.

关键词： Mixed kernel invasive weed optimization algorithm Parameter optimization Twin support vector machines

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Simultaneous Distribution Network Reconfiguration and DG Allocation for Loss Reduction by invasive weed optimization algorithm

Simultaneous Distribution Network Reconfiguration and DG All...

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Smart Grid Conference (SGC)

作者： Esmailnezhad, B. Shayeghi, H. Univ Mohaghegh Ardabili Ardebil Iran

ISBN: (纸本)9781479930395;9781479930388

Distribution Network Reconfiguration (DNR) and optimal placement of Distributed Generators (DGs) are two major approaches to reduce losses of distribution networks. In this paper a new method to reduce network loss with the simultaneous utilize of these two issues is presented. For this purpose, the DNR and determining sizing and sitting of DG is modeled as an optimization problem for minimizing the total loss of the system considering operation constraints. An evolutionary algorithm called invasive weed optimization (IWO) algorithm is used to solve this problem. Moreover, the graph theory and tree condition for a graph are used for radiality checking during the DNR problem solution. The proposed method is applied to both IEEE 33-Bus radial test system and Khoram Abad city real network. Assessment all optimization results show the effectiveness of the proposed method for loss reduction.

关键词： Distribution Network Reconfiguration Distributed Generators invasive weed optimization algorithm Loss Reduction

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optimization of airflow distribution in mine ventilation networks considering ventilation energy consumption and number of regulators

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ENGINEERING optimization 2025年

作者： Wen, Lixue Wang, Jinmiao Wang, Liguan Zhong, Deyun Liu, Yulong Cent South Univ Sch Resources & Safety Engn Changsha Peoples R China Xiangtan Univ Sch Environm & Resources Xiangtan Peoples R China Changsha DIMINE Co Ltd Changsha Peoples R China Shenzhen Zhongjin Lingnan Nonferrous Met Co Ltd Shenzhen Peoples R China

In view of the problem of high energy consumption and high control costs caused by uneven airflow distribution and unreasonable control in complex mine ventilation networks, this study takes the minimum ventilation energy consumption and number of regulators as optimization objectives to establish a multi-objective optimization model for airflow distribution in mine ventilation networks. Based on the roadway adjustable attributes and the minimum spanning tree principle, the location of regulators was reasonably determined. Moreover, this article proposes an improved invasive weed optimization (IIWO) algorithm to solve the optimization model with high coupling and nonlinearity. Compared with other algorithms, IIWO showed excellent optimization performance. IIWO was applied to optimize the airflow distribution in the mine ventilation network. The results show that the algorithm can effectively reduce the energy consumption and number of regulators of the ventilation network, and the energy saving rate of the fan is 31.78%.

关键词： Mine ventilation network airflow distribution optimization invasive weed optimization algorithm greedy differential mutation benchmark function

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