Search Results - intelligence based ((((time algorithm) OR (bat algorithm))) OR (svm algorithm))
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Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm
Published 2020“…Therefore, our proposed method partitions the given graph to sub-graphs that can be tackled independently, which reduces the computational time of finding the MDS solution. This paper investigates the swarm intelligence behaviour represented by a population-based approach called the bat algorithm (BA) to find the smallest set of nodes that dominate the graph. …”
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Hybrid bat algorithm for minimum dominating set problem
Published 2017“…This method uses population-based approach called bat algorithm (BA) which explore a wide area of the search space, thus it is capable in the diversification procedure. …”
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Time series data intelligent clustering algorithm for landslide displacement prediction
Published 2018“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
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Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy
Published 2020“…Extended Bat Algorithm (EBA) has been chosen as swarm intelligent based method for this research study. …”
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Comparative performance of machine learning algorithms for cryptocurrency forecasting
Published 2018“…Methods has been proposed to construct models including machine learning algorithms such as Neural Networks (NN), Support Vector Machines (SVM) and Deep Learning. …”
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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation
Published 2018“…Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. …”
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A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems
Published 2019“…Compared with the shark algorithm (SA), BA, weed algorithm (WA), PSO algorithm, and genetic algorithm (GA), the NHA decreased the computation time by 28%, 36%, 39%, 82%, and 88%, respectively, which represents an excellent enhancement result. …”
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
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Quantum Inspired Computational Intelligence Techniques for Combined Economic Emission Dispatch Problem
Published 2017“…Quantum computing phenomenon is integrated with swarm intelligence-based PSO and bat algorithm (BA) to make these algorithms computationally more powerful and robust.…”
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Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…In terms of computational time, compared to GS-tuned models and the respective HS hybrids, the proposed hybrid MHS-SVM and MHS-RF have reported time improvement of more than 50%, while the parallel computation have saved up approximately 80% of the computational time. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The FSR-AIRS2 is a new hybrid algorithm that incorporates the FRA, RRC, and the SVM into AIRS2 in order to produce a stronger classifier. …”
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…SVR however is inferior in accuracy and thus this paper discusses the usage of an optimized SVR with Evolved Bat Algorithm (EBA) to handle the missing value accurately with high execution time. …”
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