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An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning
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This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In order to evaluate the proposed algorithm in term of finding the best solution, six benchmark test functions are used to make a comparison between AMOPSO and the standard MOPSO. The results show that the AMOPSO has a better ability to get away from local optimums with a quickest convergence than the MOPSO. The simulation results using Matlab 2014a, indicate that this methodology is extremely valuable for every robot in multi-robot framework to discover its own particular proper pa‌th from the start to the destination position with minimum distance and time.

 

 

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Publication Date
Tue Jun 30 2015
Journal Name
College Of Islamic Sciences
The Logic of Freezers and Animals in the Holy Quran: (Objective study
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The Logic of Freezers and Animals in the Holy Quran

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Publication Date
Tue Mar 01 2016
Journal Name
International Journal Of Engineering Research And Advanced Technology (ijerat)
Speeding Up Back-Propagation Learning (SUBPL) Algorithm: A New Modified Back_Propagation Algorithm
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The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

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Publication Date
Fri Feb 28 2020
Journal Name
Neuroquantology
Studying the Swarm Parameters and Electron Transport Coefficients in N2– CH4 Mixtures Using BOLSIG+ Program
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
A Modified Strength Pareto Evolutionary Algorithm 2 based Environmental /Economic Power Dispatch
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A Strength Pareto Evolutionary Algorithm 2 (SPEA 2) approach for solving the multi-objective Environmental / Economic Power Dispatch (EEPD) problem is presented in this paper. In the past fuel cost consumption minimization was the aim (a single objective function) of economic power dispatch problem. Since the clean air act amendments have been applied to reduce SO2 and NOX emissions from power plants, the utilities change their strategies in order to reduce pollution and atmospheric emission as well, adding emission minimization as other objective function made economic power dispatch (EPD) a multi-objective problem having conflicting objectives. SPEA2 is the improved version of SPEA with better fitness assignment, density estimation, an

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Publication Date
Sun Apr 30 2017
Journal Name
Journal Of Engineering
Evaluation of Urban Planning Projects Criteria Using Fuzzy AHP Technique
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In this research,  Fuzzy Analytic Hierarchy Process technique is applied (Fuzzy AHP) which is one of  multi-criteria decision making techniques to evaluate the criteria for urban planning projects, the project of developing master plan of Al-Muqdadiyah city to 2035 has been chosen as a case study. The researcher prepared a list of criteria in addition to the authorized departments criteria and previous researches in order to choose optimized master plan according to these criteria. This research aims at employing the foundations of (Fuzzy AHP) technique in evaluating urban planning criteria precisely and flexible. The results of the data analysis to the individuals of the sample who are specialists, in this aspect.  The la

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of The College Of Education For Women
Adaptive Response and its relation to Cognitive Appraisal among Secondary School Students
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The current research's problem includes the impact of cognitive reappraisal and reformulate on self-experience of emotional response and its negative feelings and the activity of cognitive reappraisal in changing response. The aim of this research is to detect the relation between adaptive response and cognitive reappraisal upon students of secondary school, and to find differences in gender and stage. The sample contained male and female student for the year(2022-2023) and consists of (480) students (240) male and (240) female in the karkh education/ 1 To achieve this aims researcher used descriptive method and to measure the two variables researcher built a scale for adaptive response according to theory of compound emotion (Barrett,20

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Publication Date
Sun Jan 08 2023
Journal Name
Journal Of Planner And Development
Statistical Evaluation of the Planning Process and Scheduling Management for Irrigation and Drainage Projects in the Republic of Iraq
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The Research aims to investigate into reality in terms of planning and scheduling management process for sake the implementation and maintenance of irrigation and drainage projects in the Republic of Iraq, with an indication of the most important obstacles that impede the planning and scheduling management process for these projects and ways of addressing them and minimizing their effects.                                                  For the purpose of achieving the goal of the research, a sci

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Publication Date
Wed Feb 01 2023
Journal Name
Mathematical Models And Computer Simulations
Function Approximation Technique (FAT)-Based Adaptive Feedback Linearization Control for Nonlinear Aeroelastic Wing Models Considering Different Actuation Scenarios
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Publication Date
Wed Sep 08 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Strategic tax planning and its impact on reducing tax evasion
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Taxes are an essential axis in the economy as the most effective and effective economic tool in any country (economy). Expanding the scope of taxation without adequate study has produced a dangerous result with a negative impact that is almost apparent, namely (tax evasion), which stands as a barrier preventing the state from reaching Therefore, the research sought to study strategic tax planning and its importance in reducing tax evasion, and the research aims from that to prove the importance of adopting strategic planning in the field of taxes according to modern and effective scientific foundations to reduce tax evasion to enhance the achievement of tax evasion. The financing objective is in addition to the other objectives,

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Publication Date
Tue May 01 2012
Journal Name
2012 Second International Conference On Digital Information And Communication Technology And It's Applications (dictap)
The compact Genetic Algorithm for likelihood estimator of first order moving average model
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Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results

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