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45 results for “Coefficient of Determination”
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Research ArticleOpen accessEvery word in the titleEMPIRICAL DETERMINATION OF THE AVERAGE ANNUAL RUNOFF COEFFICIENT IN THE MEDITERRANEAN AREAGiovanni Grillone, Giorgio Baiamonte, Francesco D’AsaroRunoff estimation in ungauged basin is a challenge for the hydrological engineers and planners. For any hydrological study on an ungauged basin, a methodology has to be appropriately selected for the determination of runoff at its outlet. Several methods have been used to estimate the basin runoff production. In this study the empirical Kennessey method to determine average annual runoff … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 5 Dec 2013 · 8,218 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDetermination of Kinetic Correction Coefficient of Fluid Flow Using a Generic Multiple Orifice Physical Scale Model StructureEmmanuel M. AdigioProblem statement: Diesel particulate filters are fast becoming integral parts of diesel engines, light and heavy duty, due to their potential in the reduction of particulate matter from exhaust gases and their noise muffling property. Consequently, several researchers are developing mathematical models for the study of fluid flow through the filter substrate and in the aiding of filter systems design. … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 2 · 30 Jun 2009 · 7,553 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOn the Comparison of Methods of Estimating Missing Values in Rectangular Lattice DesignsAbimibola V. Oladugba, Emmanuel O. Ossai, Tobias E. UgahMissing values occur in almost all research which lead to ambiguity in data analysis. It becomes necessary that appropriate consideration is made in order to provide an efficient and valid analysis. Researchers have developed and compared a variety of methods of estimating missing values in experimental designs; however, no research work has derived and compared methods of estimating missing values, … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 11 Oct 2018 · 7,044 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 819 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Analysis of Drug Reviews: Identifying Patient Conditions, Predicting Drug Ratings, and Sentiment AnalysisRafat Hammad, Mohammad Ashraf Ottom, Ayah Bani BakerUnderstanding patients' experiences with medications is essential for improving drug effectiveness, detecting potential side effects, and enhancing overall patient satisfaction. This research investigates applying machine learning to patient drug reviews across three main tasks: Identifying patient conditions, predicting drug ratings, and performing sentiment analysis. We implemented and evaluated Convolutional Neural Networks (CNNs), Artificial Neural Networks (ANNs), and Recurrent Neural Networks … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 736 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,355 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 abstractTree Volume Prediction Model of Cupressus lusitanica Species: in North-Western Highlands of EthiopiaYishak Adgo Kassie, Abebaw Alene YallewA significant basis of raw materials for the forest products industry is provided by Cupressus lusitanica, one of the commercial timber tree species found in the forest. Accurate tree and stand volume development models are necessary for intensive forest management to yield timber. The goal of this study was to develop and validate volume equations for Cupressus lusitanica tree species … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 26 Aug 2025 · 5,936 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 abstractAutoregressive Integrate Mean Average as Approaches for Modeling Energy Production in the Electricity Network by Seasons of the Electric Energy Company in Lomé, TogoApaloo Bara Komla Kpomonè et al.The work accumulated in this article presents the results of modeling the tduction of electrical energy for the CEET network in Lomé, Togo, taking into account the seasons of the area. The objective is to evaluate the forecasts over the periods in relation to the seasons of the year. Four seasons are detected, namely: Long dry season, long rainy season, … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 4 · 20 Dec 2024 · 3,922 accessesView PDFCite