Search Results - (( java implementation path algorithm ) OR ( causing problems learning algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…However, this algorithm is well-known to have difficulties with local minima problem particularly caused by neuron saturation in the hidden layer. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Three-term backpropagation algorithm for classification problem
Published 2006“…This algorithm utilizes two term parameters which are Learning Rate, α and Momentum Factor,β. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid
Published 2022“…One of the major challenges when applying machine learning is to identify the best algorithm from a variety of algorithms to solve a problem. …”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…This proposal discusses the techniques of optimizing and deploying machine learning algorithms on embedded devices for manufacturing applications; We investigate problems of printed circuit board (PCB) defects and artificial intelligence in embedded system. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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Unified neural network controller of series active power filter for power quality problems mitigation
Published 2013“…First, Widrow-Hoff algorithm is examined and its constant learning rate is modified by adding an adaptive learning rule to change the learning rate value. …”
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Reinforcement learning based techniques in uncertain environments: problems and solutions
Published 2015“…Reinforcement learning (RL) is a well-known class of machine learning algorithms used in planning and controlling of autonomous agents. …”
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Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer
Published 2018“…Breast cancer is a considerable problem among the women and causes death around the world. …”
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Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Along with that, two algorithms have been constructed by capturing the positive correlations where the first algorithm (MLR-PC) captures the positive global correlations and the second algorithm (MLCBA) proposes an adaption of AC algorithm to handle MLC based on the positive local correlations. …”
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Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi
Published 2022“…The CNN method has been used in this study to detect children because the method can automatically learn pattern features and reduce the incompleteness caused by artificial design features. …”
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