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检索条件"主题词=Whale optimization algorithm"

共 1211 条记录，以下是301-310 订阅

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Research on selective harmonic elimination technology based on enhanced whale optimization algorithm 21

Research on selective harmonic elimination technology based ...

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21st IEEE International Conference on Mechatronics and Automation (IEEE ICMA)

作者： Li, Weijie Zhang, Wenyi Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin Peoples R China

ISBN: (纸本)9798350388084;9798350388077

The key of inverter selective harmonic elimination technology lies in solving nonlinear transcendental equations. This paper takes a two-level three-phase bridge inverter circuit as an example, establishes its mathematical model from its output voltage, then constructs an evaluation function, and verifies the feasibility of the enhanced whale optimization algorithm in a selective harmonic elimination technology through MATLAB/Simulink simulation. At the same time, the simulation results also show that the DC voltage utilization rate of the three-phase inverter controlled by the selective harmonic elimination technology based on the enhanced whale optimization algorithm can reach 1.063, which is superior to the traditional Newton iterative method and SPWM technology in DC voltage utilization rate and harmonic elimination efficiency.

关键词： Inverter selective Harmonic Elimination whale optimization algorithm Nonlinear transcendental equations

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Path Planning of Underwater Vehicles Based on Improved whale optimization algorithm 6

Path Planning of Underwater Vehicles Based on Improved Whale...

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6th International Conference on Automation, Control and Robotics Engineering (CACRE)

作者： Li, Guangqiang Dong, Wenchao Wang, Yongjie Zhu, Daqing Liu, Qi Dalian Maritime Univ Sch Marine Elect Engn Dalian Peoples R China

ISBN: (纸本)9781665435765

In order to better solve path planning problems of underwater vehicles on complicated seabed terrains under ocean currents, a global path planning method based on whale optimization algorithm (WOA) is proposed. We focus on the fixed-depth navigation, and the underwater environment is modeled based on the MAKLINK graph. Three criteria of the length, smoothness and energy cost are used to evaluate a path. Considering that the original WOA algorithm lacks of balance in the exploration and exploitation at different positions in the search space and is easy to fall into local optima, the improved whale optimization algorithm (IWOA) is presented. The proposed algorithm creates an adaptive elite set by selecting best individuals from the population, and the members of the set will be randomly selected to be combined into new individuals to guide the searching process of the proposed algorithm. The corresponding guidance strategy is that the search agents update the position directionally based on the locations and orientations of the new individuals, replacing the encircling update centered on the position of prey in the original algorithm. Dijkstra algorithm is utilized for "coarse-grained planning" of path planning, and an approach to augment the waypoints is developed to cooperate with the proposed IWOA to complete the "fine-grained planning". Above two-step planning forms the global path planning method proposed in this paper. The simulation results show that the proposed method is feasible and effective through testing under different circumstances. Compared with original WOA, paths planned by proposed method and IWOA have higher qualities, with shorter lengths, smoother paths and more energy saving.

关键词： path planning whale optimization algorithm underwater vehicles

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Improvement whale optimization algorithm Based on Mixed Strategy 15

Improvement Whale Optimization Algorithm Based on Mixed Stra...

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15th International Conference on Advanced Computational Intelligence (ICACI)

作者： Liu Yujia Tang Feng Chen Xin Jiangxi Coll Applicat Sci & Technol Sch Intelligent Mfg Engn Nanchang 330000 Jiangxi Peoples R China Jiangxi Univ Sci & Technol Sch Informat Engn Ganzhou 341000 Peoples R China Zhejiang Normal Univ Coll Math & Comp Sci Jinhua 321004 Zhejiang Peoples R China

ISBN: (纸本)9798350321456

As the original whale optimization algorithm (WOA) has the drawback of falling into local extremes, it also fails to meet the expectations in terms of convergence effect. An improved whale optimization algorithm (HWOA) based on a hybrid strategy was proposed. First, the proposed algorithm is initialized based on the Zaslayskii chaotic map to obtain a population with better ergodicity;second, The elite search base strategy is used to improve the global optimization ability of the algorithm and increase the probability of jumping out of the local extreme value;Finally, by introducing an adaptive variable speed strategy, the search ability and development capabilities of the whale optimization algorithm are effectively coordinated while retaining the advantages of the algorithm. The improved whale optimization algorithm is tested against other algorithms on 10 benchmark functions. The final results demonstrate the effectiveness of the HWOA algorithm improvement strategy and outperforms other improvement algorithms in terms of effectiveness.

关键词： whale optimization algorithm chaotic mapping elite search pool adaptive adjustment factor

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A binary Sine Cosine-Modified whale optimization algorithm for Feature Selection 4

A binary Sine Cosine-Modified Whale Optimization Algorithm f...

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IEEE 4th National Computing Colleges Conference (NCCC)

作者： Eid, Marwa M. El-kenawy, El-Sayed M. Ibrahim, Abdelhameed Delta Higher Inst Engn & Technol Mansoura Egypt Mansoura Univ Fac Engn Mansoura Egypt

ISBN: (纸本)9781728167190

The increase of many pillars within the dataset makes it needed to pick the best part of features. The feature selection approach directly influences the performance of the style in terms of integrity and computational information. The wrapper feature choice version deals with the function set to improve the category reliability. In this paper, a new wrapper feature selection binary formula is intended based upon the Sine Cosine algorithm (SCA) and a modified whale optimization algorithm (MWOA). This algorithm (Binary SC-MWOA) was associated with obtaining unassociated characteristics and selecting the optimum features. The proposed formula's attractive outcomes reveal the algorithm's performance for picking the best features. Ten different UCI Repository datasets are checked in the experiments.

关键词： optimization Meta-heuristics Feature Selection whale optimization algorithm Sine Cosine algorithm

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Tuning of SMC Parameters for Robotic Manipulator Based on whale optimization algorithm 2

Tuning of SMC Parameters for Robotic Manipulator Based on Wh...

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2nd World Robot Conference (WRC) / Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Du, Meilin Guo, Zuhua Meng, Cai Beihang Univ Sch Astronaut 37 Xueyuan Rd Beijing Peoples R China

ISBN: (纸本)9781728155524

A 2-link robotic manipulator is selected as a research instance, a sliding mode control(SMC) law is designed. Parameters tuning of sliding mode controller is converted to a nonlinear optimization problem with the objects of minimizing the trajectory tracking error and eliminating chattering of the control torques. The whale optimization algorithm (WOA) is adopted in this paper to obtain the best parameters of controller, and a comparative study with the results that are searched by particle swarm optimization (PSO) is made. Through simulation of the manipulator, control effects of the parameters obtained by the two optimization methods are compared. Research shows that WOA is a viable optimization method for parameter tuning of sliding mode control of robotic manipulator, and the optimization model proposed in this paper can effectively eliminate the chattering problem of control torques.

关键词： whale optimization algorithm Sliding Mode Control Robotic Manipulator Control Nonlinear optimization

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Comparison of Grasshopper and whale optimization algorithm for Design of FACTS Controller with Power System Stabilizer 5

Comparison of Grasshopper and Whale Optimization Algorithm f...

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5th IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC)

作者： Sahu, Preeti Ranjan Hota, Prakash Kumar Panda, Sidhartha Veer Surendra Sai Univ Technol Dept Elect Engn Burla 768018 India

ISBN: (纸本)9781728106465

Recently, Grasshopper optimization algorithms (GOA) and whale optimization algorithm (WOA) technique have significant consideration among different meta-heuristic optimization techniques. GOA is a newly proposed nature inspired algorithm based on social behavior of grasshopper. The WOA technique is also comparatively modern meta-heuristic method, which mimics the behavior of humpback whales. Both the optimization techniques are popular in industry and science mainly because of their simplicity, avoidance of local optima and gradient free mechanism. These two methods are assumed to discover an appropriate solution considering a given objective work. The major goal of this controller design is to increase the stability of power system. Here, both GOA and WOA techniques are employed to optimize the parameters of the designed static synchronous series compensator (SSSC) controller with power system stabilizer (PSS). The proposed conventional lead-lag SSSC controller with PSS are optimized by using both GOA and WOA optimization techniques and tested under single-machine infinite bus system. At last, the simulation results of both GOA and WOA techniques are verified by considering different loading conditions.

关键词： Grasshopper optimization algorithm whale optimization algorithm Flexible AC Transmission System Controller Lead-Lag Controller Power System Stability

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Automatic Shape Matching Using Improved whale optimization algorithm with Atomic Potential Function 18th

Automatic Shape Matching Using Improved Whale Optimization A...

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18th International Conference on Intelligent Computing (ICIC)

作者： Wei, Yuanfei Ling, Ying Luo, Qifang Zhou, Yongquan Guangxi Minzu Univ Xiangsihu Coll Nanning 530225 Guangxi Peoples R China Natl Univ Malaysia Fac Informat Sci & Technol Ukm Bangi 43600 Selangor Malaysia Guangxi Minzu Univ Sch Artificial Intelligence Nanning 530006 Peoples R China Guangxi High Sch Key Lab Complex Syst & Computat Nanning 530006 Peoples R China

ISBN: (纸本)9783031138324;9783031138317

This paper an improved whale optimization algorithm (IWOA) with atomic potential matching (APM) for shape matching is proposed. The optimization process of shape matching is considered as a numerical optimization problem which can be conventionally exploited by the optimization algorithms. We improved whale optimization algorithm (WOA) where our modifications add the local pollination phase from the flower pollination algorithm. Then the IWOA based atomic potential matching (APM) model for searching the optimal shape matching. The comparative experiments with other algorithms for solving three different examples of shape matching problems demonstrate the feasibility and effectiveness. Meanwhile, the proposed shape matching algorithm proved to be superior to the comparative others swarm intelligence optimization algorithms, improved quality of results in all examples and significantly improve convergence speed.

关键词： whale optimization algorithm Atomic potential matching Local pollination phase Shape matching Swarm intelligence optimization

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Design of Low-Cost Fuzzy Controllers with Reduced Parametric Sensitivity Based on whale optimization algorithm

Design of Low-Cost Fuzzy Controllers with Reduced Parametric...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： David, Radu-Codrut Precup, Radu-Emil Preitl, Stefan Szedlak-Stinean, Alexandra-Iulia Roman, Raul-Cristian Petriu, Emil M. Politehn Univ Timisoara Dept Automat & Appl Informat Timisoara Romania Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada

ISBN: (数字)9781728169323

ISBN: (纸本)9781728169323

The aim of this paper is to demonstrate the feasibility of whale optimization algorithm (WOA) in solving complex control design and tuning problems of fuzzy control systems (FCSs) with a reduced parametric sensitivity. The sensitivity analysis of these FCSs implies the use of sensitivity models defined with respect to the parametric variations of the processes. The main goal is solving the optimization problems defined for servo system processes controlled by Takagi-Sugeno-Kang proportional-integral fuzzy controllers (TSK PI-FCs), through minimization of objective functions that include the output sensitivity functions. A design method is proposed in this regard, and it is validated through experimental results using a laboratory nonlinear servo system.

关键词： experimental validation fuzzy control system parametric sensitivity whale optimization algorithm

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A Multi-Objective Optimal Vehicle Fuel Consumption Based on whale optimization algorithm 12th

A Multi-Objective Optimal Vehicle Fuel Consumption Based on ...

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12th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP)

作者： Horng, Mong-Fong Thi-Kien Dao Shieh, Chin-Shiuh Trong-The Nguyen Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung Taiwan Haiphong Private Univ Dept Informat Technol Haiphong City Vietnam

ISBN: (纸本)9783319502120;9783319502113

Due to the complex environmental constraints in the field of transport and logistics, optimization for the vehicle fuel consumption problem satisfies not only one criterion but also several criteria. In this paper, a novel multi-objective method for an optimal vehicle traveling based on whale optimization algorithm (WOA) is proposed. In the proposed method, two criteria of distance and path-travel gasoline of the vehicle traveling issue are transformed into a minimization one. The vehicle routing and traffic status in the environmental transportation are considered to model the fitness function for the solution in WOA. The path of the globally best whale in each iteration is selected, and reached by the vehicles in sequence. In addition, the information of traffic status updates to vehicle periodically times from traffic navigation system during the traveling. Series scenarios of simulations are implemented in different traffic environments for the optimal paths when the vehicles reached the destination. The results show that the proposed method provides the confirm the practicality of the model of transport and logistics, and this proposed method may be the alternative method of optimization for the vehicle traveling in the logistics.

关键词： whale optimization algorithm Vehicle fuel consumption Multi-objective optimization

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A Backbone whale optimization algorithm Based on Cross-stage Evolution 13th

A Backbone Whale Optimization Algorithm Based on Cross-stage...

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13th International Conference on Swarm Intelligence (ICSI)

作者： Yang, Xin Wang, Limin Zhang, Zhiqi Han, Xuming Yue, Lin Jinan Univ Guangzhou Peoples R China

ISBN: (纸本)9783031096778;9783031096761

The swarm intelligent algorithms (SIs) are effective and widely used, while the balance between exploitation and exploration directly affects the accuracy and efficiency of algorithms. To cope with this issue, a backbone whale optimization algorithm based on cross-stage evolution (BWOACS) is proposed. BWOACS is mainly composed of three parts: (1) adopts the density peak clustering (DPC) method to actively divide the population into several sub-populations, generates the backbone representatives (BR) during backbone construction stage;(2) determines the deviation placement (DP) by constructing the co-evolution operators (CE), the search space expansion operators (SE) and the guided transfer operators (GT) during bionic evolution strategy stage;(3) realises the bionic optimisation through DP during backbone representatives guiding co-evolution stage. To verify the accuracy and performance of BWOACS, we compare BWOACS with other variants on 9 IEEE CEC 2017 benchmark problems. Experimental results indicate that BWOACS has better accuracy and convergence speed than other algorithms.

关键词： whale optimization algorithm Density peak clustering Bionic evolution strategy

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