Search Results - (( machine loading algorithm ) OR ( machine research algorithm ))

An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms by Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain

“…In this research work, an exhaustive parametric and empirical comparative study is conducted on the SEIL dataset for the recommendation of the optimal machine learning algorithm. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation by Zhanuzak, Raiymbek, Ala'anzy, Mohammed Alaa, Othman, Mohamed, Algarni, Abdulmohsen

“…Furthermore, the EDLB algorithm enhances load balancing by 46.46%. These results highlight the effectiveness of the EDLB algorithm in addressing critical load balancing issues and surpassing existing methods. …”
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A hybrid bio-inspired and musical-harmony approach for machine loading optimization in flexible manufacturing system by Yusof, Umi Kalsom, Budiarto, Rahmat, Deris, Safaai

“…Manufacturing industries are facing fierce challenges in handling product competitiveness, shorter product cycle time and product varieties.The situation demands a need to improve the effectiveness and efficiency of capacity planning and resource optimization while still maintaining their flexibilities.Machine loading - one of the important components of capacity planning is known for its complexity that encompasses various types of flexibilities pertaining to part selection, machine and operation assignment along with constraints.Various studies are done to balance the productivity and flexibility in Flexible Manufacturing System (FMS).From the literature, researchers have developed many approaches to reach a suitable balance of exploration (global improvement) and exploitation (local improvement).We adopt a hybrid of population approaches; hybrid constraint-chromosome genetic algorithm and harmony search algorithm (H-CCGaHs), to solve this problem that aims at mapping a feasible solution to the domain problem.The objectives are to minimize the system unbalance as well as to increase the through-put while satisfying the constrains such as machine time availability and tool slots.The proposed algorithm is tested for it performance on 10 sample problems available in FMS literature and compared with existing solution approaches.…”
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Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

“…Then they are assigned to the machines according to the assignment algorithm for job combinations, which is a special integer partition algorithm. …”
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Cloud computing load balancing technique with virtual machine migration / Rabiatul Addawiyah Mat Razali by Mat Razali, Rabiatul Addawiyah

“…Based on this idea, an algorithm in activating and deciding on the virtual machine migration operation is proposed, in which the overall load balancing process could be improved. …”
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Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

“…The CMS relies on the principle of grouping machines into machine cells and grouping machine parts into part families that is named cell formation. …”
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Comparison Between the Bees Algorithm and Genetic Algorithm Model in Manpower Allocation on Cell Loading Problem by AlMahasneh, Hossam Sayel

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A Systematic Literature Review of Electricity Load Forecasting using Long Short-Term Memory by Salleh N.S.M., Suliman A., J�rgensen B.N.

“…Brain; Deregulation; Electric load forecasting; Electric power plant loads; Electric utilities; Learning algorithms; Statistical tests; Electricity load; Electricity load forecasting; Evaluation metrics; Load predictions; Long term planning; LSTM; Machine learning algorithms; Medium-term planning; Review papers; Systematic literature review; Long short-term memory…”

Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

“…In response to the unprecedented challenges posed by the COVID-19 pandemic, this research project presents a systematic approach to outbreak prediction, specifically advocating for the implementation of Support Vector Machine (SVM) algorithms. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Predicting suspended sediment load in Peninsular Malaysia using support vector machine and deep learning algorithms by Essam Y., Huang Y.F., Birima A.H., Ahmed A.N., El-Shafie A.

Dynamic load balancing algorithm based on deadline constrained in cloud environment by Mansur, Muzzammil

“…This research work implements a scheduling algorithm which balances the workload among the whole VM using last K interval and to measure makespan time as well as number task that meet their respective deadline when the resources and task rejection is increasing. …”
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Implementation of Health Monitoring System for Patients using Machine Learning Algorithms by Hariprasad, U.S., UshaSree, R.

“…We employed the Decision Tree Algorithm to train and assess a model that produced a perfection of 66.66%.…”
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Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…To achieve these goals, a cell selection algorithm is proposed that overcomes the issues of conflicts and load imbalance while reducing energy consumption. …”
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A new technique for maximum load margin estimation and prediction by Aziz N.F.A., Rahman T.K.A., Yasin Z.M., Zakaria Z.

“…This paper presents the application of Fast Artificial Immune System (FAIS) for maximum load margin estimation and hybrid Fast Artificial Immune Support Vector Machine (FAISVM) for maximum load margin prediction. …”

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

“…Additionally, the machine learning models successfully predict the optimal critical buckling load under mechanical and thermal loading conditions. …”
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Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy by Yap K.S., Yap H.J.

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Training of interval type-2 fuzzy logic system using extreme learning machine for load forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…Application of the developed model to electricity load forecasting is another novelty of the research work. …”
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Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb, Mushtaq, Mansor, Muhamad, Razali, Ramdan, Daniyal, Hamdan, A. F. Yahaya, Jabbar

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