Search Results - parallel using ((window algorithm) OR (learning algorithm))*

Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network by Abduh Kaid, Monir Abdullah

“…This routing problem is an NPhard problem. Many algorithms are designed by many researchers to perform this routing such as window method, sequential algorithm, degree-descending algorithm, simulated annealing algorithm, genetic algorithm and ant colony algorithm.This thesis explores two approaches, sequential and parallel approaches. …”
Get full text
Get full text

Parallel Optical Window Algorithm Applied to Optical Multistage Interconnection Network by Othman, Mohamed, Abdullah, Monir, Johari, Rozita

“…In this paper, a new parallel algorithm of the window method is developed called the Balanced Parallel Window Method (BPWM) algorithm. …”
Get full text
Get full text

Line clipping based on parallelism approach and midpoint intersection by Hattab, Adel Salem Abdullah, Yusof, Yuhanis

“…The main property is considered in this algorithm is the parallelism with window boundary to define the clipped line.For parallel lines with window boundaries no need to use intersection point method to find the coordinates of the end points of the clipped line.Midpoint algorithm is used to determine the intersection point with the clipped boundary for non-parallel lines. …”
Get full text
Get full text
Get full text

Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm by Khoo, Thau Soon

“…Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). …”
Get full text
Get full text

Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
Get full text
Get full text

Efficient hardware design for palm-dorsa vein image enhancement by Jusoh@Yusoff, Suhaimi Bahisham

“…For hardware design of thinning, parallel pipelined with Concurrent Condition Check Unit hardware architecture has been developed to enable the parallelism of the thinning algorithm. …”
Get full text
Get full text
Get full text

Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi by Hayawi, Mustafa Jabbar

“…An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN. …”
Get full text
Get full text

Fast and efficient sequential learning algorithms using direct-link RBF networks by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George

“…The dynamic DRBF network is trained using the recently proposed decomposed/parallel recursive Levenberg Marquardt (PRLM) algorithm by neglecting the interneuron weight interactions. …”
Get full text
Get full text

Parallel backpropagation neural network training for face recognition by Omarov B., Suliman A., Tsoy A.

“…In this paper, we describe implementation of ANN training process using backpropagation learning algorithm for exploiting the high performance SIMD architecture of GPU using CUDA. …”

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…The results showed that using canopy as a preprocessing step cut the time it proceeds to deal with the significant number of power load abnormalities found in parallel using a fast density peak dataset and the time it proceeds for the k-means algorithm to run. …”

Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

“…The methodology was benchmarked using popular data sets from UCI machine learning repository.…”
Get full text
Get full text
Get full text

Resource Minimization in a Real-time Depth-map Processing System on FPGA by Ngo, Huy Tan, Hamid, Nor Hisham, Sebastian , Patrick, Yap, Vooi Voon

“…Depth-map algorithm allows camera system to estimate depth. It is a computational intensive algorithm, but can be implemented with high speed on hardware due to the parallelism property. …”
Get full text
Get full text

A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

“…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
Get full text
Get full text
Get full text
Get full text

A parallel-model speech emotion recognition network based on feature clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

“…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
Get full text
Get full text
Get full text

Grid portal technology for web based education of parallel computing courses, applications and researches by Alias, Norma, Islam, Md. Rajibul, Mydin, Suhaimi, Hamzah, Norhafiza, Safiza Abd. Ghaffar, Zarith, Satam, Noriza, Darwis, Roziha

“…This paper proposes the web service education technology for postgraduate parallel computing course, e-learning students, real-time solutions and for supervising projects related to the application of parallel computing, that focuses on the fundamental principles to parallel computer architecture, multimedia, communication cost, master-worker model, parallel algorithm, web services and performance evaluations. …”
Get full text
Get full text

A parallel ensemble learning model for fault detection and diagnosis of industrial machinery by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Sim, Seera, Manjeevan, Chee, Peng Lim

“…Accordingly, this paper proposes a new parallel ensemble model comprising hybrid machine and deep learning for undertaking FDD tasks. …”
Get full text
Get full text
Get full text

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

“…In this paper, a parallel deep learning-based community detection method in large complex networks (CNs) is proposed. …”
Get full text
Get full text
Get full text
Get full text

Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath. by Hasan, Nurul

“…Key features of this paper are the use of the domain decomposition and encapsulated message passing to enable execution in parallel. …”
Get full text
Get full text

Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
Get full text
Get full text
Get full text

The forecasting of poverty using the ensemble learning classification methods by Zamzuri, Muhammad Haziq Adli, Nadilah, Sofian, Hassan, Raini

“…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
Get full text
Get full text
Get full text