Search Results - (( java implementation path algorithm ) OR ( programming learning acs 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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Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin
Published 2014“…In addition, the MLFNN utilized solar irradiance (SI), ambient temperature (AT) and module temperature (MT) as its inputs and AC power as its output. Additionally, the optimal population size, absorption confession, learning algorithm and type of transfer functions in FA were also investigated in this study. …”
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Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging
Published 2022“…Nonetheless, a robust DCNN model was achieved as there is no sign of the model’s over-or under-ftting upon the learning process. Conclusions: The application of digital imaging and deep learning techniques used by the DP-AC and convolutions neural network algorithms to segment and identify premolars provides promising results for semi-automated forensic dental staging in the future…”
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HELM based Reinforcement Learning for Goal Localization
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Firefly algorithm-based neural network for GCPV system output prediction / Nor Syakila Mohd Zainol Abidin
Published 2014“…Therefore, this thesis presents a hybrid Firefly Algorithm (FA)–based MLFNN for predicting the AC power output from a grid-connected photovoltaic (GCPV) system. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad
Published 2022“…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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