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Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun
Published 2015“…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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2
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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3
Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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4
Multi-state PSO GSA for solving discrete combinatorial optimization problems
Published 2016“…The experimental results showed the newly introduced multi-state PSO GSA are promising compared to binary particle swarm optimization (BPSO) and binary gravitational search algorithm (BGSA) for the TSP and consistently outperformed simulated annealing (SA), genetic algorithm (GA), and BPSO for the ASP in finding optimal solutions.…”
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5
Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. The second modification develops a new position update mechanism using the Bat Algorithm movement. …”
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6
An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
Published 2015“…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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An Assembly Sequence Planning Approach with a Rule-based Multi-state Gravitational Search Algorithm
Published 2015“…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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A review of crossover methods and problem representation of genetic algorithm in recent engineering applications
Published 2020“…Genetic algorithm (GA) is a popular technique of optimization that is bio-inspired and based on Charles Darwin's proposed principles of natural genetics and natural selection theories. …”
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A Multi-State Gravitational Search Algorithm for Combinatorial Optimization Problems
Published 2015“…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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Binary search algorithm-based maximum power point tracking for photovoltaic system under partial shaded conditions
Published 2018“…This paper presents the study on the application of Binary Search Algorithm (BSA) to determine the maximum power point under partially shaded photovoltaic system. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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A novel multi-state gravitational search algorithm for discrete optimization problems
Published 2015“…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
Published 2015“…The performance of the proposed distance evaluated SKF (DESKF) is compared against two other discrete population-based optimization algorithms, namely, binary particle swarm optimization (BPSO) and binary gravitational search algorithm (BGSA). …”
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Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur
Published 2007“…In sorting algorithm, we focused on quick sort, heap sort, merge sort, bubble sort, insertion sort and selection sort while in searching algorithm we focused on binary search and sequential search. …”
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17
Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system
Published 2021“…In this paper, the Dijkstra-ant colony algorithm (ACO) with binary search tree (BST) has been proposed. …”
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Taguchi's T-method with nearest integer-based binary bat algorithm for prediction
Published 2023“…In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi�s T-method. …”
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
Published 2017“…The performance of the clustering algorithm gets even worse if it relies on actual data and many clustering algorithms are often faced with conflict in handling high dimensional data. …”
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Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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