Search Results - (( intelligence task scheduling algorithm ) OR ( intelligence based training algorithm ))

Processing time estimation in precision machining industry using AI / Lim Say Li by Lim, Say Li

“…Neural Network (NN) model is chosen as the artificial intelligence approach used in this research. Levenberg-Marquardt algorithm is used as the training algorithm. …”
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Two objectives big data task scheduling using swarm intelligence in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke, Islam, Shayla, Zarir, Abdullah Ahmad

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Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

“…The main part of RMS is the scheduler algorithm which has the responsibility to map submitted tasks to available resources. …”
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Efficiency and accuracy of scheduling algorithms for final year project evaluation management system by Loo, Chang Herng, Muhammad Zulfahmi Toh, Abdullah, Ahmad Fakhri, Ab. Nasir, Nur Shazwani, Kamaruddin, Nur Hafieza, Ismail

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An improved fair nurse scheduling optimisation using particle swarm intelligent technique by Ramli, Mohamad Raziff

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Evaluate the performance of university timetabling problem with various artificial intelligence techniques by Hooi, Charmaine Wai Yee

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Application of an evolutionary algorithm-based ensemble model to job-shop scheduling by Tan, Choo Jun, Neoh, Siew Chin, Lim, Chee Peng, Hanoun, Samer, Wong, Wai Peng, Loo, Chu Kiong, Zhang, Li, Nahavandi, Saeid

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Task scheduling in cloud computing using Harris-Hawk Optimization by Iza A. A. Bahar, Azali Saudi, Abdul Kadir, Syed Nasirin Syed Zainol Abidin, Tamrin Amboala, Esmadi Abu Bin Abu, Abdullah B. Mohd. Tahir, Suddin Lada

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Managing risk in production scheduling under uncertain disruption by Sarker, Ruhul, Essam, Daryl, Kamrul Hasan, S.M., Karim, A.N. Mustafizul

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Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

“…Computing intelligence is a soft-computing subset of artificial intelligence referring to the potential of a computer to gain knowledge from an experimental observations or specific task. …”

Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

“…The ANNs trained by the optimized DA also achieve higher accuracy than those trained by some other swarm intelligence algorithms. …”
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Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System by Ismail, F. B., Al-Kayiem, Hussain H.

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Intelligent dashboard with speech enhancement by Abdul Rahman, Abdul Wahab, Tan, Eng Chong, Abut, Huseyin

“…Numerous asynchronous scheduling tasks necessitate the architecture to be re-configurable. …”
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Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh D., Ismail F.B., Shakir Nasif M.

Integration of dual intelligent algorithms in shunt active power filter by Abdul Rahman, Nor Farahaida, Mohd Radzi, Mohd Amran, Mariun, Norman, Che Soh, Azura, Abd Rahim, Nasrudin

“…This paper presents an integration of dual intelligent algorithms: artificial neural network (ANN) based fundamental component extraction algorithm and fuzzy logic based DC-link voltage self-charging algorithm (fuzzy self-charging algorithm), in a three-phase three-wire shunt active power filter (SAPF). …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

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A New Grid Resource Discovery Framework by Mahamat Issa, Hassan, Azween , Abdullah

“…Resource discovery (RD) is an important key issue in grid systems since resource reservation and task scheduling are based on it. This paper proposes a novel semantic-based scalable decentralized grid RD framework. …”
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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

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