Search Results - intelligence based ((bat algorithm) OR (svm algorithm))*
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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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HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION
Published 2023“…The Bat Algorithm is a population-based meta-heuristic algorithm for solving continuous optimization problems. …”
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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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Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm
Published 2020“…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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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study
Published 2024“…RF was the most precise algorithm for predicting grades A, B, and C, followed by LR, DT, and SVM. …”
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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
Published 2018“…On the other hand, the hybridization of SVM with other methods such as SVM-Genetic Algorithm (SVM-GA), SVM-Artificial Immune System (SVM-AIS), SVM-AIRS and fuzzy support vector machine (FSVM) had great performances achieving better results in terms of accuracy, sensitivity and specificity.…”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms
Published 2021“…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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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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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation
Published 2018“…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
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Comparative performance of machine learning algorithms for cryptocurrency forecasting
Published 2018“…Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. …”
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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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Dual-tone multifrequency signal detection using support vector machines
Published 2023Subjects:Conference paper -
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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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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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