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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

Q-REINFORCEMENT LEARNING BASED MULTI-AGENT BELLMANFORD ROUTING ALGORITHM FOR SMART MICROGRID COMMUNICATION NETWORK by SINGH, NIHARIKA

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Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

Multi-agent reinforcement learning for Bai ethnic traditional dwelling protection in Dali : cultural identity-oriented community relationship optimization and urbanization adaptati... by Xiaohua, Qian, Neilson Ilan, Mersat, Haslina, Hashim, Bemen Wong, Win Keong

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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment by Murad, Saydul Akbar, Zafril Rizal, M. Azmi, Muzahid, Abu Jafar Md, Bhuiyan, Md Khairul Bashar, Saib, Md, Rahimi, Nick, Prottasha, Nusrat Jahan, Bairagi, Anupam Kumar

“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach by Shabbir Ahmed, Omar, Syed Mohamed Ali, Jaffar, Aabid, Abdul, Hrairi, Meftah, Mohd Yatim, Norfazrina Hayati

“…Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. …”
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PREDICTIVE MODELING OF DIMENSIONAL ACCURACIES IN 3D PRINTING USING ARTIFICIAL NEURAL NETWORK by Sivaraos, Kumaran K., Dharsyanth R., Amran M., Shukor S.M., Pujari S., Ramasamy D., Vatesh U.K., Mahdi Al-Obaidi A.S.H., Ramesh S., Lee K.Y.S.

“…The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”

Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller by Sepeeh, Muhamad Syazmie

“…The function of the ANN was to improve speed-tracking performance, and the learning rate of the ANN inside the indirect FOC’s structure trained using the Levenberg-Marquardt (LM) algorithm was varied in order to increase speed-tracking accuracy when combined with the improved ANN speed controller. …”
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Predictive modeling of dimensional accuracies in 3D printing using artificial neural network by Subramonian, Sivarao, Kumaran, K., Dharsyanth, R., Md Ali, Mohd Amran, Salleh, Mohd Shukor, Pujari, Satish, Ramasamy, Devarajan, Vatesh, Umesh Kumar, Mahdi Al-Obaidi, Abdulkareem Sh, Ramesh, S., Lee, Kit Yee Sara

“…The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

“…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models. by Kwad, Ayad Mahmood

“…This research introduces a developed method for online system identification based on the Hammerstein and Wiener nonlinear block-oriented structure with the artificial neural networks (NN) advantages and recursive weighted least squares algorithm for optimizing neural network learning in real-time. …”
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Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process by Kong, Hong Shim

“…The developed neural-fuzzy model should be further considered in a wider range of real-world machining processes for learning and prescribing knowledge.…”
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