Search Results - (( simultaneous implementation learning algorithm ) OR ( java implementation path algorithm ))

Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

“…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 by Mohammad Ata, Karimeh Ibrahim

“…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 by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

“…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 by Adam, Mohd Syafiq

“…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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Design and development of cooperative simultaneous localization and mapping integrated with neural network for mobile robot by Jamaludin, Amirul

“…Autonomous cooperating mobile robots is one of technological advancement in enabling autonomy in search and rescue task (SaR). While, simultaneous localization and mapping (SLAM) algorithm is one of a key element to enable autonomous navigation. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Mobile robot positioning system by Khairulnizam Othman

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Distributed Multi-Feature Recognition Scheme for Greyscale Images by Muhamad Amin , Anang Hudaya, Khan, Asad I.

“…Furthermore, our approach implements single-cycle learning known as collaborative-comparison learning where new patterns are continuously stored using collaborative approach without affecting previously stored patterns. …”
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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA by Zahari, Taha, Farzad, Tahriri, Siti Zawiah, Md Dawal

“…A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. …”
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A modified group authentication scheme for machine type communication in LTE/LTE-a networks by Ismail, Haqi Khalid

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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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Hyperparameter tuning in deep learning using NSGA-III: a Multi-Objective perspective by Mohamad Rom, Abdul Rahman

“…This thesis proposes and implements a novel framework: the Multi-Objective NSGA-III-DL model, wherein the Non-Dominated Sorting Genetic Algorithm III (NSGA-III) is directly infused into the deep learning optimization process. …”
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A study of the high-performance computing parallelism in solving complexity of meteorology data and calculations by Noor Affendi, Mohd Ridhuan, Hussin, Masnida, Hasan, Dana

“…Further issues can be studied for integrating big data analytics and machine learning into HPC computing architectures.…”
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Feature and Instance selection via cooperative PSO by Syed Ahmad, Sharifah Sakinah

“…Although, some work has been done to implement the feature and instance selection simultaneously, this work has focused on mainly the classification problem. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

“…The RSNN implements a novel approximation transform. The basic design for the network is provided together with the learning rules. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

“…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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A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow by Harold Harrison, Mazlina Mamat, Farah Wong, Hoe Tung Yew, Racheal Lim, Wan Mimi Diyana Wan Zaki

“…An optical flow-based preprocessing algorithm synchronized motion features in recorded video inputs with measured vibration labels, improving measurement accuracy. …”
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Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust by Arshad, U., Taqvi, S.A.A., Buang, A.

“…The experimental data has been divided into the training set and testing set in the proportion of 85 (for training) and 15 (for testing) respectively. A machine learning artificial neural network approach with Levenberg-Marquardt algorithm is implemented to obtain the predictive model for MIT of aluminium dust for both the particle size ranges (100â��63 µm, 50â��32 µm). …”
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Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust by Arshad, U., Taqvi, S.A.A., Buang, A.

“…The experimental data has been divided into the training set and testing set in the proportion of 85 (for training) and 15 (for testing) respectively. A machine learning artificial neural network approach with Levenberg-Marquardt algorithm is implemented to obtain the predictive model for MIT of aluminium dust for both the particle size ranges (100â��63 µm, 50â��32 µm). …”
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Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

“…Simultaneously the approach adheres to an essential criterion of the original method. …”
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