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Fireflyclust: an automated hierarchical text clustering approach by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…The proposed clustering method operates based on five phases: data pre-processing, clustering, item re-location, cluster selection and cluster refinement. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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Assessment of suitable hospital location using GIS and machine learning by Almansi, Khaled Y. M.

“…First, the conditioning factors were optimized and ranked to identify and select the most correlated factors to predict the suitability of a hospital site by applying the correlation feature selection (CFS) algorithm and the greedy-stepwise search method. …”
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Harmony search algorithm for curriculum-based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…In this paper, harmony search algorithm is applied to curriculum-based course timetabling.The implementation, specifically the process of improvisation consists of memory consideration, random consideration and pitch adjustment.In memory consideration, the value of the course number for new solution was selected from all other course number located in the same column of the Harmony Memory.This research used the highest occurrence of the course number to be scheduled in a new harmony.The remaining courses that have not been scheduled by memory consideration will go through random consideration, i.e. will select any feasible location available to be scheduled in the new harmony solution. …”
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Harmony search algorithm for curriculum-based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…In this paper, harmony search algorithm is applied to curriculum-based course timetabling.The implementation, specifically the process of improvisation consists of memory consideration, random consideration and pitch adjustment.In memory consideration, the value of the course number for new solution was selected from all other course number located in the same column of the Harmony Memory.This research used the highest occurrence of the course number to be scheduled in a new harmony.The remaining courses that have not been scheduled by memory consideration will go through random consideration, i.e. will select any feasible location available to be scheduled in the new harmony solution.Each course scheduled out of memory consideration is examined as to whether it should be pitch adjusted with probability of eight procedures. …”
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Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

“…The chapter also carries out an analytical review of three main searching algorithms namely, generate and test, uninformed search, and hill climbing search algorithms. …”
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Edge Detection Algorithm For Image Processing Of Search And Rescue Robot by A/L Sivem, Prasanthran

“…This project entitled “ Edge Detection Algorithm for Image Processing of Search and Rescue Robot ” has its primary purpose to identify an optimum edge detection algorithm for image processing of search and rescue robot. …”
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

“…To overcome the problems, this research work has proposed few modified and new ABC variants; Gbest Influenced-Random ABC (GRABC) algorithm systematically exploits two different mutation equations for appropriate exploration and exploitation of search-space, Multiple Gbest-guided ABC (MBABC) algorithm enhances the capability of locating global optimum by exploiting so-far-found multiple best regions of a search-space, Enhanced ABC (EABC) algorithm speeds up exploration for optimal-solutions based on the best so-far-found region of a search-space and Enhanced Probability-Selection ABC (EPS-ABC) algorithm, a modified version of the Probability-Selection ABC algorithm, simultaneously capitalizes on three different mutation equations for determining the global-optimum. …”
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A Multidimensional Search Space Using Interactive Genetic Algorithm by Farooq, H., Zakaria, M.N., Hassan, M.F., Sulaiman, Suziah

“…This paper applied an Interactive Genetic Algorithm (IGA) technique to design an visualization environment for search space. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques by Lipu M.S.H., Hussain A., Saad M.H.M., Hannan M.A.

Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun by Harun, Hazaruddin

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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation by Alrosan, Ayat, Alomoush, Waleed, Norwawi, Norita, Alswaitti, Mohammed, Makhadmeh, Sharif Naser

Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun by Harun, Hazaruddin

“…The Linear-PSO algorithm was the first version of improvement. However due to the longer time required for complete execution of this algorithm, the Binary Search technique was integrated and a new version of the algorithm was developed, namely the Linear-PSO with Binary Search (LPBS) algorithm. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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Document clustering based on firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

“…Among multi-objective evolutionary algorithms proposed in the literature, particle swarm optimization (PSO)-based multi-objective (MOPSO) algorithm has been cited to be the most representative. …”
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Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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