Search Results - (( using set method algorithm ) OR ( based optimization modified algorithm ))
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1
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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2
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In addition, two novel Jaya-based methods namely, the modified Jaya (MJaya) algorithm and quasi-oppositional modified Jaya (QOMJaya) algorithm are proposed to solve different MOOPF problems. …”
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3
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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4
Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
Published 2022“…Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. …”
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5
Memoryless modified symmetric rank-one method for large-scale unconstrained optimization
Published 2009“…Computational results, for a test set consisting of 73 unconstrained optimization problems, show that the proposed algorithm is very encouraging. …”
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6
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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7
Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…The solution’s construction is modified using the concept of global best operator that is used in the Particle Swarm Optimization (PSO). …”
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8
New Quasi-Newton Equation And Method Via Higher Order Tensor Models
Published 2010“…By using a new equation, the BFGS method is modified. …”
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9
Logistic regression methods for classification of imbalanced data sets
Published 2012“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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10
Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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11
Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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12
A hybrid of ant colony optimization, genetic algorithm and flux balance analysis for optimization of succinic acid production in Escherichia coli
Published 2023“…Hence, there is a lot of ongoing research on E. coli by using in silico methods. Researchers build computational models of E. coli to analyze and modify their metabolic network. …”
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13
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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14
Curve fitting by rational cubic Bézier with C1 and G1 continuity using metaheuristics methods
Published 2019“…Rational cubic Bézier curves are used to approximate the data sets while minimizing the least-squares error function using different metaheuristics algorithms. Those metaheuristics algorithms are Harmony Search, Genetic Algorithm, Particle Swarm Optimization and Modified Harmony Search. …”
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15
Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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16
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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17
Common benchmark functions for metaheuristic evaluation: a review
Published 2017“…Algorithms that perform well on a set of numerical optimization problems are considered as effective methods for solving real-world problems. …”
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18
Modelling of multi-robot system for search and rescue
Published 2023“…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
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Final Year Project / Dissertation / Thesis -
19
Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
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20
A hybrid adaptive harmony search with modified great deluge algorithm for school timetabling
Published 2025“…This research enhances HSA by hybridizing it with the Great Deluge Algorithm (GDA) using a four-phase methodology. In Phase 1, heuristic rules refine the time assignment stage to improve an existing construction algorithm. …”
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