Search Results - (( swarm optimization mining algorithm ) OR ( parameter optimization method algorithm ))

Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”

Accelerated mine blast algorithm for ANFIS training for solving classification problems by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…It has outperformed Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and their variants when solving various engineering optimization problems. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

“…The performance of the ANFIS optimization by AMBA is compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), MBA and Improved MBA (IMBA), respectively. …”
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Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem by Wong, Jerng Foong

“…It is also used extensively in experiments to test the performances of metaheuristic algorithms and their hybrids. For example, Tabu Search (TS) has been successfully hybridized with other techniques, including particle swarm optimization (PSO) algorithm and the two-stage TS algorithm to solve MKP. …”
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Evaluation of data mining models for predicting concrete strength by Wong, Chuan Ming

“…The Particle Swarm Optimization algorithm is able to generate optimal values for the concrete features that maximizes the strength of concrete. …”
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A novel approach to data mining using simplified swarm optimization by Wahid, Noorhaniza

“…In this thesis, a novel Simplified Swarm Optimization (SSO) algorithm is proposed as a rule-based classifier and for feature selection. …”
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs by Sadiq, Ali Safa, Alkazemi, Basem Y., Mirjalili, Seyedali, Noraziah, Ahmad, Khan, Suleman, Ihsan, Ali, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

“…In order to improve the accuracy of artificial neural network (ANN) classifier, we have integrated our proposed hybrid magnetic optimization algorithm-particle swarm optimization (MOA-PSO) technique. …”
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Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing. by Abubaker, Ahmad Asad

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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs by Sadiq, Ali Safaa, Alkazemi, Basem, Mirjalili, Seyedali, Ahmed, Noraziah, Khan, Suleman, Ali, Ihsan, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

“…In order to improve the accuracy of artificial neural network (ANN) classifier, we have integrated our proposed hybrid magnetic optimization algorithm-particle swarm optimization (MOA-PSO) technique. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

“…Therefore, it can be solved by using population-based techniques such as Genetic Algorithm and Particle Swarm Optimization. This paper proposes the integration of feature reduction and data reduction for fuzzy modeling using Cooperative Binary Particle Swarm Optimization (CBPSO). …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

“…The proposed algorithm and mutation mechanism showed optimal performances as compared to the existing algorithms. …”
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Feature Selection And Enhanced Krill Herd Algorithm For Text Document Clustering by Abualigah, Laith Mohammad Qasim

“…In this study, a new method for solving the TD clustering problem worked in the following two stages: (i) A new feature selection method using particle swarm optimization algorithm with a novel weighting scheme and a detailed dimension reduction technique are proposed to obtain a new subset of more informative features with low-dimensional space.…”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…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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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…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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Feature Selection with Harmony Search for Classification: A Review by Norfadzlan, Yusup, Azlan, Mohd Zain, Nur Fatin Liyana, Mohd Rosely, Suhaila Mohamad, Yusuf

“…From the review, feature selection with HS algorithm shows a good performance as compared to other metaheuristics algorithm such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).…”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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