78 results for “RMSE”

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Research ArticleOpen accessIn the keywordsFuel Prediction Model for Driving Patterns Using Machine Learning TechniquesManjunath TK, Ashok Kumar PSIn recent years, the demand for fuel efficiency has become a crucial aspect of the automotive industry. Predicting fuel economy accurately is essential for optimizing vehicle performance and reducing environmental impact. This proposed model presents a machine learning-based approach for developing a fuel prediction model using the real dataset. The model aims to predict fuel efficiency for different drivers by … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,480 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsEffects of Environmental Noises on Fundamental Frequency Contours of Thai Expressive SpeechSuphattharachai Chomphan, Chutarat ChompunthProblem statement: The expressive speech of Thai had been studied for a short period of time. An important feature of speech was fundamental frequency (F0) which defines the human speech prosody. It could be used to distinguish the difference between several types of expressive speech. The environmental noises affect the F0 contour for Thai dialects as concluded in the previous … …American Journal of Applied Sciences, Vol. 9, Issue 8 · 28 Jun 2012 · 6,907 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsValidation of the Ceres-Wheat for Prediction of Wheat Varieties in Irrigation and Terminal Drought StressFarzad Paknejad, Fatemeh Majidi Fakhr, Seied Mehdi MirtaheriProblem statement: Crop growth models have many potential uses for crop managements. Approach: In order to evaluation of CERES-Wheat model on five varieties of winter wheat in Karaj weather condition in Full Irrigation (FI) and Stop Irrigation (SI) after flowering until final growth stage an experiment conducted in shape of split plot in based on randomize complete block design with … …American Journal of Agricultural and Biological Sciences, Vol. 7, Issue 2 · 16 Mar 2012 · 7,723 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsIntelligence System for Software Maintenance Severity PredictionParvinder Singh Sandhu, Sunil Kumar, Hardeep SinghThe software industry has been experiencing a software crisis, a difficulty of delivering software within budget, on time, and of good quality. This may happen due to number of defects present in the different modules of the project that may require maintenance. This necessitates the need of predicting maintenance urgency of the particular module in the software. In this paper, … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,941 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsOptimal Parameter Tuning in a Predictive Nonlinear Control Method for a Mobile RobotD. Hazry, M. SugisakaThis study contributes to a new optimal parameter tuning in a predictive nonlinear control method for stable trajectory straight line tracking with a non-holonomic mobile robot. In this method, the focus lies in finding the optimal parameter estimation and to predict the path that the mobile robot will follow for stable trajectory straight line tracking system. The stability control contains … …American Journal of Applied Sciences, Vol. 3, Issue 4 · 30 Apr 2006 · 7,083 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHybrid Enhanced Neighbourhood and Latent Factor Model for Cold-Start RecommendationsAmritha P, Rajkumar KKAmong different recommendation strategies, collaborative filtering remains a commonly utilized method for generating personalized suggestions. The traditional collaborative algorithms face performance declines due to the sparse rating of data and the item cold-start problem. To overcome these challenges, this paper introduces a novel hybrid model called HCE-KNNCF (Hybrid Cognition-Enabled K-Nearest Neighbor Collaborative Filtering). The proposed model generates predicted rating by … …Journal of Computer Science, Vol. 22, Issue 9 · 21 Sep 2026 · 622 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAdaptive Cross-Validation Under Concept Drift for Time Series ForecastingKunjira Kingphai, Prapakorn Kanjina, Kamol Sanittham, Wacharong WongsanurakTime-series forecasting often involves non-stationary data, making i.i.d. validation unreliable and fixed-window protocols vulnerable to leakage and biased error estimates. We propose Adaptive Time-Series Cross-Validation (ATSCV), a drift-aware evaluation framework that uses statistical change-point detection to partition each series into contiguous, approximately stationary regimes, followed by forward-chaining folds that respect those boundaries. By aligning train–validation splits with distributional changes (with … …Journal of Computer Science, Vol. 22, Issue 7 · 7 Jul 2026 · 1,488 accessesView PDF Cite

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 PDF Cite

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 PDF Cite

Research ArticleOpen accessIn the abstractLatent Feature-Based Trust-Aware Model for Service Delegation in Social Internet of Things (SIoT)Rahul, Venkatesh, Satish B BasapurThe integration of social networking concepts into the Internet of Things (IoT) paradigm has given rise to Social IoT (SIoT) ecosystems, aiming to address challenges related to network navigation, service discovery, and service composition. A fundamental issue in SIoT is the careful selection of trustworthy devices that provide services. A service provider can offer multiple and diverse services, and different … …Journal of Computer Science, Vol. 21, Issue 12 · 9 Jan 2026 · 1,802 accessesView PDF Cite