Search Results - (( using function search algorithm ) OR ( based classification problems algorithm ))
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1
Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…This paper proposes a new metaheuristic search algorithm called Cuckoo Search (CS) based on Cuckoo bird’s behavior to train Elman recurrent network (ERN) and back propagation Elman recurrent network (BPERN) in achieving fast convergence rate and to avoid local minima problem. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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3
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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4
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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5
Enhanced Automated Framework For Cattle Tracking And Classification
Published 2022“…Computer vision-based methods could be used to monitor each individual cows. …”
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6
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Then a review of different methods currently available that can be used to solve clustering and classification problems is also given. …”
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7
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…Secondly, a new DE algorithm (ARDE-SPX) is introduced that automatically adapts a repository of DE strategies and parameters control schemes to avoid the problems of stagnation and make DE respond to a wide range of function characteristics at different stages of evolutionary search. …”
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8
Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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9
Tree-based contrast subspace mining method
Published 2020“…Genetic algorithm has been widely used to find global solution to optimization and search problem. …”
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10
Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…The proposed methods show superior results in several benchmark function tests. As for EMG feature selection, the proposed algorithms are evaluated using the EMG data acquired from the publicly access EMG database. …”
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11
Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm
Published 2010“…In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. …”
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12
Short Text Classification Using An Enhanced Term Weighting Scheme And Filter-Wrapper Feature Selection
Published 2018“…In the second stage, grey wolf optimization (GWO) algorithm, a new heuristic search algorithm, uses the SVM accuracy as a fitness function to find the optimal subset feature.…”
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13
RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
Published 2018“…The efficiency of the proposed method is verified by means of simulation on four classification problems. The results show that the computational efficiency of the proposed method was better than the conventional BP algorithm.…”
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14
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…The performance of most metaheuristic algorithms depends on parameters whose settings essentially serve as a key function in determining the quality of the solution and the efficiency of the search. …”
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15
An efficient anomaly intrusion detection method with feature selection and evolutionary neural network
Published 2020“…The proposed search algorithm uses mutation to more accurately examine the search space, to allow candidates to escape local minima. …”
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16
Hybrid conjugate gradient using exact line search in photovoltaic system / Muhammad Ariiq Iqbaal Azizul Firdaus
Published 2025“…At last, PRPLS is implemented in photovoltaic system, specifically in the maximum power point tracking (MPPT) algorithm. This study shows the effectiveness of PRPLS in solving problem of maximizing the power output generated by the photovoltaic system.…”
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Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification
Published 2017“…Based on the occurrences of the best result obtained by an algorithm across different test functions; it is proven that the proposed method outperforms standard GA. …”
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19
Named entity recognition using a new fuzzy support vector machine.
Published 2008“…In our method we have employed Support Vector Machine as one of the best machine learning algorithm for classification and we contribute a new fuzzy membership function thus removing the Support Vector Machine’s weakness points in NER precision and multi classification. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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