Search Results - (( using optimization method algorithm ) OR ( data application optimisation algorithm ))

Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

“…Global optimisation is a method to identify the optimal kinetic parameter in ordinary differential equation. …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

“…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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B-spline curve fitting with different parameterization methods by Kheng, Jia Shen

“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

“…The OCGA is compared with other well known local search method namely dynamic length tabu search, randomised steepest descent method, and other variants of genetic algorithms using extensive data sets collected from the literatures. …”
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Leveraging transfer learning and label optimization for enhanced traditional Chinese medicine ner performance by Saidah Saad, Zikun, Huang

“…By retraining the model using the optimised training set, an optimal F1 measure of 92.7% was achieved. …”
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Passive congregation theory for particle swarm optimization (PSO): An application in reservoir system operation by Hossain M.S., Mohd Sidek L.B., Marufuzzaman M., Zawawi M.H.

Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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A survey on improvement of Mahalanobis Taguchi system and its application by Tan L.M., Wan Muhamad W.Z.A., Yahya Z.R., Junoh A.K., Azziz N.H.A., Ramlie F., Harudin N., Abu M.Y., Tan X.J.

Asset liability management model: The case of selected Islamic banks in Malaysia / Chong Hui Ling by Chong , Hui Ling

“…Specifically, this research has been conducted with the core objective to develop a customised programming model for multi-purpose optimisation using this penalty cost method that ties together divergent objectives unique to Islamic banks. …”
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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach by Waidah Ismail, Ismail Ahmed Al-Qasem Al-Hadi, Crina Grosan, Rimuljo Hendradi

Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor by Mohamad Nor, Ahmad Azhari

“…The early design of the augmented reality application exhibits potential for real-time data visualisation, providing insights into optimal detection distances and angles. …”
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar by Noorsal, Emilia, Osman, Muhammad Khusairi, Mokhtar, Norfadzilah

“…The input and output neurons used for the three networks were 5 neurons. The optimum structure of the neural network was determined by trial and error method to obtain the optimized hidden neuron and weight values. …”
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Development of tool life prediction model of TiAlN coated tools during the high speed hard milling of AISI H13 steel by Amin, A. K. M. Nurul, Hafiz, A.M. Khalid, Lajis, M. A.

“…RSM also reduces total number of trials needed to generate the experimental data in order to response model. The application of RSM in machining parameter optimization was first reported to be used by SM.Wu, 1965. …”
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Smart grid: Bio-inspired algorithms energy distributions for data centers by Woo, Yu Hang

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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad by Mehdi , Jahanirad

“…The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm by Mohamad Fadzil, Nur Hamisha Helanie

“…Future work may focus on integrating real-time data, adjusting algorithm parameters and hybridizing ABC algorithm with other metaheuristics to further improve performance.…”
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