Search Results - (( developing neural solution 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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Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network by Karim, Syed Anayet

“…In the current Artificial Neural Network research development, symbolic logical structure plays a vital role for describing the concept of intelligence. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli by Hakim Adenan, Muhammad Nasrul, Zolkapli, Maizatul

“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis by Ashraf Osman, Ibrahim, Siti Mariyam, Shamsuddin, Abdulrazak, Yahya Saleh, Ahmed, Ali, Mohd Arfian, Ismail, Shahreen, Kasim

“…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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Development of computer aided three-dimensional geometric modeler based on designer's idea in twodimensional by Haron, Habibollah

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Artificial neural network and inverse solution method for assisted history matching of a reservoir model by Negash, B.M., Vel, A., Elraies, K.A.

“…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman by Seman, Noraini

“…However, due to the stochastic nature of this algorithm, the learning process can reach an optimal solution with much higher probability than many standard neural network techniques.…”
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A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm by Yahaya, Nor Zaiazmin

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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

“…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions by Alsa’di, Kawthar, Nik Long, Nik Mohd Asri, Senu, Norazak, Eshkuvatov, Z.K.

“…A new generalized Gronwall inequality in the sense of the Riemann–Liouville conformable integral is established and utilized to prove the priori bounded of the solution. A hybrid technique, combining a polynomial neural network (PNN) with an extreme learning machine algorithm without using any activation functions, is developed. …”
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Steady state security analysis using artificial neural network by Mohd Nor, Nurul Huda

“…The performance of the developed model is compared with the unified neural network trained with the full feature set. …”
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