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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…Since the direct application of the firefly algorithm cannot generate connected topologies, outputs from the firefly algorithm were used as an initial input material distribution for the OC method. …”
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…Furthermore, a comparative study was carried out to show the effectiveness of the proposed algorithms over other well-known methods in terms of computational time (speed) and function values. …”
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3
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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4
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…The performance of the method is evaluated based on the ability to reduce function value after each iteration, ability to attain the lowest function value when applied to solve the well-known zebra-strip problem. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…As a result, the highest average accuracy generated which is 96.91% by using WBCD dataset. The average accuracy of Bat Algorithm is comparing with other methods. …”
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Undergraduates Project Papers -
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A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa
Published 2007“…A large nimiber of techniques, such as Neurofuzzy algorithm methods are used to produce an efficient and effective system. …”
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7
Position control of robot manipulator: Design a novel SISO adaptive sliding mode fuzzy PD fuzzy sliding mode control.
Published 2011“…Compare and evaluate proposed method and sliding mode algorithms under disturbance. …”
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Evaluating the effectiveness of integrated benders decomposition algorithm and epsilon constraint method for multi-objective facility location problem under demand uncertainty
Published 2017“…To do this, Monte Carlo method with uniform function is used, then the stability of the proposed method towards demand uncertainty is shown. …”
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Dissimilarity algorithm on conceptual graphs to mine text outliers
Published 2009“…In Comparison to other text outlier detection method, this approach managed to capture the semantics of documents through the use of CGs and is convenient to detect outliers through a simple dissimilarity function.Furthermore, our proposed algorithm retains a linear complexity with the increasing number of CGs.…”
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The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga
Published 2016“…Secondly, we compared the performance of our new algorithm pdAPSO with APSO, and PSO using 7 benchmark functions. …”
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11
Common benchmark functions for metaheuristic evaluation: a review
Published 2017“…In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. …”
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Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm
Published 2013“…The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…Lastly, in order to externally judge the validity of these types of clustering algorithms, there is a need for a method to correctly and efficiently evaluate their variant multiclass clustering results. …”
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14
Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. …”
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Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
Published 2016“…The modified RTS algorithm also performed better compared to the existing heuristic methods. …”
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Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity
Published 2014“…Passive method involves the use of enclosures, barriers and silencers but is ineffective at low frequency noise (below 500Hz). …”
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17
Tree-based contrast subspace mining method
Published 2020“…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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An experimental study of modified black hole algorithms
Published 2018“…The algorithms are evaluated based on unimodal, multimodal, hybrid, and composite functions in CEC2014 benchmark test functions. …”
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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20
A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Methods: It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. …”
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