Search Results - machine ((loading algorithm) OR (((means algorithm) OR (((_ algorithm) OR (based algorithm))))))

Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations by Nouri, Hossein, Tang, Sai Hong

“…The BFO algorithm is used to create machine cells and part families. …”
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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.

“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”

Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia by Zaini, Farah Anishah, Sulaima, Mohamad Fani, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia by Sulaima, Mohamad Fani, Zaini, Farah Anishah, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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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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Sensorless control system for assistive robotic ankle-foot by Al Kouzbary, Mouaz, Abu Osman, Noor Azuan, Wahab, Ahmad Khairi Abdul

“…Both estimation algorithms are built using C-code and assessed in MATLAB Simulink. …”
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Analysis Of Large In-Plane Displacement And Strain In Rubber Using 2-D Scanner-Based Digital Image Correlation by Pang, Goh Ching

“…The images were scanned and processed to obtain displacement, strain, load and stress data. The displacement data were obtained by using the incremental image correlation algorithm. …”
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Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer by Salleh N.S.M., Suliman A., J�rgensen B.N.

“…Brain; Errors; Forecasting; Learning algorithms; Mean square error; Memory architecture; Network architecture; Smart meters; Time series; Demand-side; Electricity load; Error values; Load predictions; Machine learning algorithms; Mean absolute error; Mean squared error; Prediction errors; Regression problem; Times series; Long short-term memory…”

Optimal short term load forecasting using LSSVM and improved BFOA considering Malaysia pandemic disrupted situation by Zaini, Farah Anishah

“…Inaccurate forecasts can have substantial economic consequences, especially during peak load periods. Due to that reason, in this study, the hybrid forecasting model based on the Least Square Support Vector Machine (LSSVM) and Improved Bacterial Foraging Optimization Algorithm (IBFOA) is developed to perform an accurate STLF and applied to load in Peninsular Malaysia during the pandemic disrupted situation. …”
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NEXT-HOUR ELECTRICITY PRICE FORECASTING USING LEAST SQUARES SUPPORT VECTOR MACHINE AND GENETIC ALGORITHM by Razak I.A.W.A., Abidin I.Z., Siah Y.K., Sulaima M.F.

“…This is due to the fact that only two algorithms were used (LSSVM and GA), with the load and HOEP for the week preceding the forecasting hour as the inputs. …”

A review energy-efficient task scheduling algorithms in cloud computing by Atiewi S., Yussof S., Ezanee M., Almiani M.

“…Algorithms; Energy efficiency; Internet protocols; Multitasking; Network management; Scheduling; Scheduling algorithms; Datacenter; DVFS; Energy efficient; GreenCloud; Task-scheduling; Virtual machines; Virtualizations; Cloud computing…”

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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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Specifically, the PSO algorithm achieved a mean surface roughness improvement of 0.44% over GA, and 1.1% and 1.23% over ACO and FA, respectively. …”
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Book recommendation system using content-based filtering / Amalin Aliesya Mohd Azmi by Mohd Azmi, Amalin Aliesya

“…This is attributed to the intricacy of the content-based filtering algorithm, necessitating a substantial computational load on the central processing unit of a computer. …”
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An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

“…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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A novel hybrid metaheuristic algorithm for short term load forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Yuhanis, Yusof, Syafiq Fauzi, Kamarulzaman

“…With respect to that matter, this study presents a hybrid Least Squares Support Vector Machines (LSSVM) with a rather new Swarm Intelligence (SI) algorithm namely Grey Wolf Optimizer (GWO). …”
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Short term forecasting based on hybrid least squares support vector machines by Zuriani, Mustaffa, M. H., Sulaiman, Ernawan, Ferda, Noorhuzaimi, Mohd Noor

“…This study assesses the performance of each hybrid algorithms based on three statistical indices viz. Mean Square Error (MSE), Root Mean Square Percentage Error (RMSPE) and Theil’s U which is realized on raw and normalized data set. …”
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Dynamic load balancing algorithm based on deadline constrained in cloud environment by Mansur, Muzzammil

“…The Performance of cloud depends on the task scheduling as well as load balancing. Cloud Service Provider (CRP) provides services on demand to the users, as the application as well as the numbers of users are gradually growing over the cloud environment which leads to the increasing in the workload that are deployed over the virtual machine (VM). …”
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