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10 results for “Load forecasting”
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Research ArticleOpen accessPhrase in the titleElectrical Load Forecasting Using Artificial Neural Network: The Case Study of the Grid Inter-Connected Network of Benin Electricity Community (CEB)Adekunlé Akim Salami, Ayité Sénah Akoda Ajavon, Koffi A. Dotche, Koffi-Sa BedjaThe low rate of electrification seems challenging in many West African countries and many strategies are underway to improve upon. In this regard, the target of achieving the universal access and services calls for a stable and reliable electrical network. Forecasting of electrical load on a connected grid network is very delicate and requires tremendous task from the utilities (billing … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 2 · 11 Apr 2018 · 9,143 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleElectricity Load Forecasting based on Framelet Neural Network TechniqueMohammed K. AbdLoad forecasting is very essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of a power system. This study shows Electricity Load Forecasting modeling based on Framelet Neural Network Technique (FNN) for Baghdad City. Framelet technique is implemented to the time series data, decomposing the data into number of Framelet coefficient signals. The decomposed signals … …American Journal of Applied Sciences, Vol. 6, Issue 5 · 31 May 2009 · 8,274 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleShort-Term and Medium-Term Load Forecasting for Jordan's Power SystemI. Badran, H. El-Zayyat, G. HalasaSeveral electric power companies are now forecasting electric loads based on conventional methods. However, since the relationship between loads and factors influencing these loads is nonlinear, it is difficult to identify its nonlinearity by using conventional methods. Most of papers deal with 24-h-ahead load forecasting or next day peak load forecasting. These methods forecast the demand power by using forecasted … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 7,081 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleForecasting Peak Load Electricity Demand Using Statistics and Rule Based ApproachZ. Ismail, A. Yahya, K. A. MahpolProblem statement: Forecasting of electricity load demand is an essential activity and an important function in power system planning and development. It is a prerequisite to power system expansion planning as the world of electricity is dominated by substantial lead times between decision making and its implementation. The importance of demand forecasting needs to be emphasized at all level as … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 7,936 accessesView PDFCite
Research ArticleOpen accessIn the abstractFL-CARE: Federated Learning-Based Contention-Aware and Energy-Balanced Routing for Dense FANETsHalimjon Khujamatov, Elyanora Jolimbetova et al.In dense multi-drone FANET environments, routing efficiency is often reduced due to constant competition for a wireless channel, frequent changes in network topology, and uneven energy consumption between UAV nodes. These factors lead to a decrease in the packet delivery ratio, an increase in delays on the busiest or most unstable routes, and a reduction in the total network lifespan. … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvergence of GenAI and RPA: A Digital Heaven in Supply Chain Optimization ProcessSaurabh A. Pahune, Zahid Akhtar, Manoj Chandrasekharan et al.One of the most groundbreaking advances in the field of intelligent automation is the merging of Generative Artificial Intelligence (GenAI) and Robotic Process Automation (RPA). This combination unlocks previously unachievable capabilities in automation. RPA (software bots) improves speed and operational efficiency by automating rule-based tasks, Standard Operating Procedures (SOPs), and repetitive workflows. At the same time, it minimizes manual labor … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Feb 2026 · 2,040 accessesView PDFCite
Research ArticleOpen accessIn the abstractFUZZY MODEL OPTIMIZATION FOR TIME SERIES DATA USING A TRANSLATION IN THE EXTENT OF MEAN ERRORNurhayadi, Subanar, Abdurakhman, Agus Maman AbadiRecently, many researchers in the field of writing about the prediction of stock price forecasting, electricity load demand and academic enrollment using fuzzy methods. However, in general, modeling does not consider the model position to actual data yet where it means that error is not been handled optimally. The error that is not managed well can reduce the accuracy of … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 2 Jun 2014 · 6,733 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetention Pond Sediment Accumulation Prediction using Monte Carlo SimulationSupiah Shamsudin, Abd Rashid Mohd Darom, Irma Norazurah Mohamad, Azmi Ab RahmanProblem statement: A study in Malaysia had been carried out to predict the sediment accumulation in urban detention ponds. Suspended sediment is pollutant of primary concern to the river that results in adverse environmental effect. Detention pond becomes a practical approach to this problem. Suspended sediment that settled in stormwater detention pond, can bring effect to the detention pond functions. … …American Journal of Environmental Sciences, Vol. 8, Issue 1 · 30 Jan 2012 · 7,528 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting and Modelling Electricity Demand Using Anfis PredictorM. Mordjaoui, B. BoudjemaProblem statement: Load forecasting plays an important task in power system planning, operation and control. It has received an increasing attention over the years by academic researchers and practitioners. Control, security assessment, optimum planning of power production required a precise short term load forecasting. Approach: This study tries to combine neural network and fuzzy logic for next week electric load … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 14 Sep 2011 · 7,811 accessesView PDFCite
Research ArticleOpen accessIn the abstractTime Series Forecasting by using Seasonal Autoregressive Integrated Moving Average: Subset, Multiplicative or Additive ModelSuhartonoProblem statement: Most of Seasonal Autoregressive Integrated Moving Average (SARIMA) models that used for forecasting seasonal time series are multiplicative SARIMA models. These models assume that there is a significant parameter as a result of multiplication between nonseasonal and seasonal parameters without testing by certain statistical test. Moreover, most popular statistical software such as MINITAB and SPSS only has facility … …Journal of Mathematics and Statistics, Vol. 7, Issue 1 · 29 Jan 2011 · 18,295 accessesView PDFCite