Search Results - (( evolution optimization svm algorithm ) OR ( using factor path algorithm ))
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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A-star (A*) algorithm implementation for robotics path planning navigation
Published 2018“…This thesis is about the implementation of Astar (A*) algorithm as path planning algorithm used in robotics navigation. …”
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Undergraduates Project Papers -
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Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries
Published 2016“…The path computed using the classic Dijkstra's algorithm is the shortest; however, it may not be the most feasible. …”
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Conference or Workshop Item -
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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New algorithm for autonomous dynamic path planning in real-time intelligent robot car
Published 2017“…Different algorithms have been used to address this problem by considering the optimal path with minimum cost; however, these algorithms did not consider the execution time to find such path. …”
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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Conference Paper -
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A Continuous Overlay Path Probing Algorithm For Overlay Networks
Published 2013“…Several experiments were carried out using the OMNeT++ simulation framework. The designed algorithm was evaluated using experimental data. …”
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Thesis -
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…However, this assumption may lead to inaccurate secondary path model. In this work, the modelling of acoustic path using FIR filters is incorporated for both algorithms for Wiener-Hammerstein structure. …”
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Thesis -
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers
Published 2009“…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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Thesis -
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Enhancing performance of global path planning for mobile robot through Alpha–Beta Guided Particle Swarm Optimization (ABGPSO) algorithm
Published 2025“…Experiments were carried out in four different layouts related to path-planning environments, and comparisons were made with various existing path-planning algorithms. …”
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Indoor navigation system using Dijkstra’s algorithm for emergency situation: article / Mohd Faizulhayad Mashuri
Published 2015“…Route planning using Dijkstra’s algorithm can produce better accuracy and more reliable in indoor environment since the only factor taken into account is the weight for each path.…”
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Resource-Efficient Coverage Path Planning for UAV-Based Aerial IoT Gateway
Published 2023“…The EECPP is composed of two algorithms: the Stop Point Prediction Algorithm using K-Means, and Path Planning Algorithm using Particle Swarm Optimization. …”
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Reducing Iteration Using Candidate List
Published 2008“…The principle of cooperation and the behavior of a single ant finding path has been the backbone in this algorithmic development. …”
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Conference or Workshop Item -
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Book Section -
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Range sensor based local path planning algorithm for mobile robot in unknown static environment with beacon / Wan Ahmad Jailani Wan Ngah
Published 2013“…PointsBug is then compared with TangentBug because it is the best among The Bug Algorithm family using the range sensor for distance, duration, speed and reachability.…”
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Thesis -
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Associated Factors of Cardiovascular Diseases in Pakistan: Assessment of Path Analyses Using Warp Partial Least Squares Estimation
Published 2020“…The information on demographic, SE, modifiable and clinical factors of CVDs was recorded. Warp partial least squares (PLS) based on warp 3 algorithm was used to estimate the simultaneous linear and non-linear path coefficients of the proposed model of study. …”
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