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检索条件"主题词=whale optimization algorithm"

共 1217 条记录，以下是321-330 订阅

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Parameter Estimation of Software Reliability Growth Models by A Modified whale optimization algorithm 17

Parameter Estimation of Software Reliability Growth Models b...

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17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)

作者： Lu, Kezhong Ma, Zongmin Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Jiangsu Peoples R China Chizhou Univ Coll Comp Sci Chizhou 247100 Anhui Peoples R China

ISBN: (纸本)9781538674451

Software reliability growth models (SRGMs) are non-linear in nature, so they are difficult to estimate the proper parameters. An estimation method based on modified whale optimization algorithm (MWOA) in which parameters are estimated is discussed in this paper. The proposed MWOA shows significant advantages in handling variety of modeling problems such as the exponential model (EXPM), power model (POWM) and delayed S-shaped model (DSSM). However, the fitting error of a single model is relatively large. In view of the different growth characteristics at each stage of the model, a three-stage software reliability growth model is proposed in this paper. MWOA is used to estimate the parameters of three-stage software reliability models. Experimental results show that the fitting accuracy of three-stage model is significantly less than that of a single model. MWOA with the three-stage model can provide a better estimate of the software faults.

关键词： Software Reliability Growth Models Parameter Estimation whale optimization algorithm Three-stage Model

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Solving 0/1 Knapsack Problem using Opposition-based whale optimization algorithm (OWOA) 19

Solving 0/1 Knapsack Problem using Opposition-based Whale Op...

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8th International Conference on Software and Computer Applications (ICSCA)

作者： Alamri, Hammoudeh S. Zamli, Kamal Z. Ab Razak, Mohd Faizal Firdaus, Ahmad Univ Malaysia Pahang Fac Comp Syst & Software Engn Pahang Malaysia

ISBN: (纸本)9781450365734

The 0/1 Knapsack problem is one of the most popular real-world optimization problems that arise in searching space and finding the most optimum solution. Theoretically, the optimum solution problem of the 0/1 Knapsack requires suitable technique to explore the search space effectively. Practically, as many metaheuristic algorithms, whale optimization algorithm (WOA) may fail in local optimum solution. This paper proposes Opposition-based whale optimization algorithm (OWOA) to optimize solution problem in 0/1 Knapsack. The OWOA has been tested original WOA by using twenty cases of Knapsack problem and against other metaheuristic algorithms such as (CGMA) and HS-Jaya. The experimental results indicate a significant performance of the optimization solution and stabilization with minimal standard deviation value. This shows that the OWOA improved the original version WOA and has promising result in comparison with other existing algorithms.

关键词： 0\1 knapsack WOA whale optimization algorithm optimization Metaheuristic Real-World optimization Problem

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Aero-engine Performance optimization Based on whale optimization algorithm 36

Aero-engine Performance Optimization Based on Whale Optimiza...

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第36届中国控制会议

作者： Xinge Huang Rui Wang Xudong Zhao Kaijian Hu School of Aeronautics and Astronautics Dalian University of Technology School of Control Science and Engineering Dalian University of Technology

ISBN: (纸本)9781538629185

Under the goal of pursuing safety,aero-engine is optimized by using an optimization algorithm to improve its performance and the comprehensive performance of the airplane.A nonlinear programming model is established to optimize the acceleration progress of a certain turbofan engine,where the rotor speed is involved in the objective ***,a novel nature-inspired optimization algorithm,called whale optimization algorithm（WOA）,which is used to solve the optimization problem of the *** results show that the WOA has a strong border search capacity and the engine’s acceleration capability has been improved.

关键词： Aero-engine optimization whale optimization algorithm

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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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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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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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Autonomous Mission Planning for Multi-Agile Earth. Observation Satellites Using whale optimization algorithm

Autonomous Mission Planning for Multi-Agile Earth. Observati...

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Chinese Automation Congress (CAC)

作者： Gao, Xinzhou Zhang, Haibo Yu, Tianhang Ma, Guangfu Gao, Duozhi Harbin Inst Technol Dept Control Sci & Engn Harbin Peoples R China Beijing Inst Control Engn Beijing Peoples R China Southwest Univ Dept Elect Informat Engn Chongqing Peoples R China

ISBN: (纸本)9781728176871

In this paper, the whale optimization algorithm is used to realize the mission planning of Multi-Agile Earth Observation Satellites for multiple target points. First of all, in the face of the observation problem of multi-satellite multi-target points, the fitness function, which satisfies the constraints faced by satellites when observing target points, is proposed in this paper. Secondly, in order to solve the task allocation problem of Multi-satellite to Multi-target points, a task allocation method based on the maximal time window is proposed in this paper. Next, the new whale optimization algorithms that have emerged in recent years is introduced in this paper. Considering that there has been no research on applying this algorithm to the mission planning problem so far, this paper proposes a method to map its iterative formula from the real number domain to the observation sequence domain based on the iterative characteristics of the whale optimization algorithm. This method enables the whale optimization algorithm to realize the iteration of the satellite observation sequence. Finally, the effectiveness of the whale optimization algorithm in sohing the multi-satellite multi-target points planning problem is verified by simulation experiments.

关键词： mission planning and allocation agile earth observation satellite whale optimization algorithm

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Electrical Parameters Extraction of Diode Using whale optimization algorithm 2

Electrical Parameters Extraction of Diode Using Whale Optimi...

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2nd International Conference on Electrical Engineering and Automatic Control (ICEEAC)

作者： Garoudja, Elyes Filali, Walid Oussalah, Slimane Lekoui, Fouaz Amrani, Rachid Ctr Dev Technol Avancees CDTA Plateforme Technol Microfabricat Cite 20 Aout 1956 Algiers 16081 Algeria Ctr Dev Technol Avancees CDTA Div Microelect & Nanotechnol Cite 20 Aout 1956 Algiers 16081 Algeria Ctr Dev Technol Avancees CDTA Div Milieux Ionises & Laser Cite 20 Aout 1956 Algiers 16081 Algeria Univ Benyoucef Benkhedda Alger 1 Dept Sci Matiere Algiers Algeria

ISBN: (纸本)9798350349740;9798350349757

In this paper, we propose a new method based on an heuristic algorithm, which is called whale optimization algorithm (WOA) to extract the main electrical parameters of a diode, such as saturation current, ideality factor, and series resistance. WOA is an efficient optimization algorithm that imitates the humpback whales natural hunting strategy. Three operators are used to mimic humpback whales behaviors of bubble-net foraging, surrounding, and searching for prey. The findings of the suggested model are compared with analytical and experimental current-voltage data, and they are shown to be in good agreement.

关键词： diode I-V characteristic heuristic algorithm whale optimization algorithm parameters extraction

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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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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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