Search Results - (( based interpolation 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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Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

“…Unmanned aerial vehicles (UAVs) may address these issues. Machine learning algorithms (MLs) can predict rice biomass from UAV-based vegetation indices (VIs). …”
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Adaptive GRNN for the modelling of dynamic plants by Yusof, Rubiyah, Khalid, Marzuki, Teo, Lian Seng

“…These adaptation strategies are formulated based on the inherent advantageous features found in GRNN, such as highly localised pattern nodes, good interpolation capability, instantaneous learning, etc.. …”
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Mortality Trends and Its Impact on the Pension Liabilities by Rose Irnawaty Ibrahim

Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

“…Most ensemble learning approaches are based on the assumption of linear combination, which is not valid due to differences in data types. …”
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Small target detection of Unmanned Aerial Vehicles based on GDWNet in the digital economy by Zhang, Yan, Zhang, Jing, Mustaffa, Mas Rina

“…During the feature fusion stage, DySample is employed to generate content-aware offsets through learning. This approach effectively breaks the fixed interpolation rules of traditional upsampling methods, enabling more dynamic, flexible, and semantically rich upsampling of the input feature maps, thereby improving the quality of feature integration. …”
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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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Kaedah Kolorimetri untuk Analisis Kuantitatif Kapsaisin Secara Pencaman Corak Menggunakan Jaringan Neural Tiruan by Mat Arip, Mohamad Nasir, Ahmad, Musa, Mokhtar, Ahmed Mahir, Taib, Mohd. Nasir, Heng, Lee Yook

“…A three layer feed-forward neural network was used and network training was performed by using back propagation algorithm. For the determination of capsaicin, a neural network with 20 hidden neurons, 0.00001% learning rate and trained over 47,738 cycles produced the best result. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

“…These results show that,for all the arrays (2D and 3D) except 3D pole - dipole data, resilient propagation is the most efficient algorithm for training the DC resistivity data. In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo

ReSTiNet : On improving the performance of Tiny-YOLO-Based CNN architecture for applications in human detection by Sumit, Shahriar Shakir, Awang Rambli, Dayang Rohaya, Mirjalili, Seyedali, Ejaz, Muhammad Mudassir, Miah, Md Saef Ullah

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