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45 articles for “mean absolute error”

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Research ArticleOpen accessIn the abstractComparative Analysis of Five Decomposition Techniques for Monthly Rainfall Time Series from 1991 to 2020 in Guinea (West Africa)Noukpo Médard Agbazo, Oumar Keita, Alpha Oumar Baldé et al.The selection of an optimal time series decomposition’ technique is crucial for enhancing rainfall prediction by using sophisticated methods as deep learning hybrid approaches. This study evaluates the effectiveness of five times series decomposition techniques in analyzing monthly rainfall datasets across Guinea geographical regions (Lower-Guinea (Boké, Conakry, Kindia), Middle-Guinea (Labé, Mamou), Upper-Guinea (Faranah, Kankan) and Forest-Guinea (Nzérékoré)) and identifies the … …American Journal of Applied Sciences, Vol. 22, Issue 1 · 27 Jan 2026 · 3,040 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrop Yield Prediction in Niger Using Machine Learning TechniquesMahaman Lawali Inoussa Garba, Naroua Harouna, Chaibou Kadri et al.Agriculture is the most impactful sector on Niger's economic growth. Stresses related to climate change and the environment are leading to a continuous decline in crop yield. Accurate crop yield forecasting is of paramount importance for farmers, government, policy makers, and other stakeholders to make most appropriate decisions regarding resource allocation and food security. This study examines the power of … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 5,792 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrediction of Physicochemical Parameters in a Rainwater Harvesting and Treatment System Modeled Using the Yahtun Algorithm in Native Communities of Northern PeruEli Morales-Rojas, Edwin Adolfo Díaz Ortiz, José Emmanuel Cruz de La Cruz et al.The inhabitants of the native communities of northern Peru do not have drinking water systems, generating serious health impacts. In this sense, rainwater harvesting systems have become an alternative for these areas. Therefore, the objective of this study was to predict the physicochemical parameters in a rainwater collection and treatment system, modeled by means of a novel “Yahtun” algorithm. The … …OnLine Journal of Biological Sciences, Vol. 25, Issue 1 · 13 Feb 2025 · 5,149 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultiple Linear Regression to Predict Electrical Energy Consumption Based on Meteorological Data: Application to Some Sites Supplied by the CEB in TogoApaloo Bara Komla Kpomonè et al.The prediction model developed in this article is based on the use of meteorological variables to estimate the consumption of electrical energy at the substations of the Electric Community of Benin. The objective is to predict this consumption in order to adapt production to it. The posts (Lomé Aflao, Légbasito, and Lomé port) are the targets that were used in … …American Journal of Applied Sciences, Vol. 21, Issue 1 · 10 Jun 2024 · 5,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Model of Corn Commodity Production in Indonesia: Production and Operation Management-Quantitative Method (POM-QM) SoftwareAsriani, Dhian Herdhiansyah, Wa Embe, LM Fid AksaraFood is essential for humans. In addition to being consumed, it can also be a valuable commodity for economic purposes through the production of food crops. Therefore, this study aims to model the forecasting of maize production in Indonesia using Production and Operations Management-Quantitative Method (POM-QM) software. The uniqueness of this research lies in its innovative approach to predicting corn … …Journal of Computer Science, Vol. 20, Issue 4 · 20 Feb 2024 · 6,150 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Oceanographic Data for Prediction of the Potential of Marine ResourcesDenny Arbahri, Oky Dwi Nurhayati, Imam MuditaMarine data and information are very important for human survival, therefore this data and information is attractive to investors because of the potential economic value. This data and information has been difficult to obtain, the solution to overcome this is by analyzing oceanographic data for 2009-2019 collected from the marine database belonging to the Agency for the Study and Application … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,970 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Observation Study for Cold and Freezing Injury of Sugarcane Based on China Meteorological Administration Land Data Assimilation System, CLDAS Temperature DataYanli Chen, Yongming Luo et al.Based on the China meteorological administration Land Surface Data Assimilation System (CLDAS), the CLDAS temperature product is examined and analyzed using remote sensing information, and a revised temperature model is established for the monitoring and evaluation of sugarcane chilling and freezing damage. The results show that: (1) The CLDAS temperature products are highly positively correlated with the measured temperatures of … …American Journal of Biochemistry and Biotechnology, Vol. 19, Issue 4 · 21 Dec 2023 · 4,995 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzy Logic-Based Truck Demand Computational ModelAnugrah Mauludin, Ditdit Nugeraha UtamaTrucking is one of the essential aspects linking suppliers and customers in many countries. Services at a trucking service provider will be based on a first-come-first-served basis. When a customer contacts a trucking service provider, there is a possibility that all the truck units owned are in fact being used to serve other customers causing potential delays in their delivery … …Journal of Computer Science, Vol. 19, Issue 9 · 19 Aug 2023 · 5,468 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 2-Tier Stacking Ensemble Classifier for Disease ClassificationK. Sukanya Varshini, R. Annie UthraDiarrhea, dysentery, and dehydration are top of the list of high mortality-causing diseases in children under the age group of five. Despite the tremendous growth of machine learning in the field of medical research, still, some areas remain untouched, especially, the pediatric department. Since medical data is used in the proposed work, even a slight increase in the accuracy of … …Journal of Computer Science, Vol. 19, Issue 7 · 7 Jun 2023 · 5,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Anomaly Detection Approach for Nifty Stocks using Machine Learning for Construction of Efficient Portfolio to Reduce Losses and Protect GainsVirrat Devaser, Priyanka ChawlaMachine Learning is the most essential and widely utilized methodological approach these days for performing, organizing, and analyzing data using a variety of approaches to produce correct and efficient results. Machine learning methodologies are also applicable to stock markets, which have grown multi-fold in recent years, and with the amount of money involved, the possibility of manipulation is always present … …Journal of Computer Science, Vol. 18, Issue 5 · 6 Jun 2022 · 6,443 accessesView PDFCite