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57 articles for “Predictive State”
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Research ArticleOpen accessIn the keywordsINCORPORATING PRIOR KNOWLEDGE INTO TEMPORAL DIFFERENCE NETWORKSBritton Wolfe, James HarpeDeveloping general purpose algorithms for learning an accurate model of dynamical systems from example traces of the system is still a challenging research problem. Predictive State Representation (PSR) models represent the state of a dynamical system as a set of predictions about future events. Our work focuses on improving Temporal Difference Networks (TD Nets), a general class of predictive state … …Journal of Computer Science, Vol. 10, Issue 11 · 18 Dec 2014 · 7,837 accessesView PDFCite
Research ArticleOpen accessIn the abstractUMPM-Net: A Multimodal Deep Learning Framework for Colorectal Cancer PrognosisK. Muthuchamy, S K. Piramu PreethikaColorectal cancer (CRC) is one of the most common cancers worldwide, for which early prediction of patient outcomes is important for personalised treatment planning and to improve survival. However, current prediction systems are limited in the fact that they are based on single-modality data and cannot capture the complex interactions between clinical, imaging, and genomic factors. To overcome these shortcomings, … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 613 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Laboratory Measured and PVTP Software DataOluwasanmi Samuel Teniola, Mercy Isaiah OkegbemiCubic Equations of State (EOS), including the Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK) models, are foundational in petroleum engineering for modeling the thermodynamic behavior of hydrocarbon systems. These EOS are widely used to predict phase behavior and Pressure-Volume-Temperature (PVT) properties, which are crucial for reservoir simulation, production forecasting, and enhanced oil recovery. However, their predictive accuracy diminishes when applied to complex … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 20 Dec 2025 · 2,761 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Approaches for the Prediction of Gas Turbine TransientsArnaud Nguembang Fadja, Giuseppe Cota, Francesco Bertasi et al.Gas Turbine (GT) emergency shutdowns can lead to energy production interruption and may also reduce the lifespan of a turbine. In order to remain competitive in the market, it is necessary to improve the reliability and availability of GTs by developing predictive maintenance systems that are able to predict future conditions of GTs within a certain time. Predicting such situations … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 7,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,751 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Model Predictive Control System Design and Implementation for Unmanned Ground VehiclesSai Charan Dekkata, Sun Yi, MA Muktadir et al.Autonomous ground robots autonomously are being used inthe places where it is very hazardous for human beings to reach and operate,such as nuclear power plants and chemical industries. The aim of the researchpresented here is to develop a control system that enables such ground robotsnavigate autonomously with various sensors as the depth camera, 2D scanninglaser, 3D Lidar, GPS, and IMU. … …Journal of Mechatronics and Robotics, Vol. 6, Issue 1 · 27 Oct 2022 · 6,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractResearch on the Link Between Economic Development Variables and the Rate of Access to Drinking Water in Rural Senegal Using Machine LearningAnabilaye Moussa Coly, Alioune Ly, Ndolane Diouf et al.After pre-processing a set of data collected from Senegalese state structures, official United Nations (UN), and world bank sites and after replacing missing values by interpolation using the mean between two values, we study the effect of macroeconomic development variables on the rate of access to drinking water in rural Senegal. To do this, we use Machine Learning (ML) techniques … …American Journal of Applied Sciences, Vol. 20, Issue 1 · 20 Dec 2023 · 6,204 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 632 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Steering and Adaptive Cruise Control for Autonomous Vehicles Using Model Predictive ControlSai Charan Dekkata, Sun YiThe research on autonomous vehicles was started nearly a century ago but the major parts of significant advance have been done over the past few decades. In this paper, designing and simulating of a Model Predictive Controller (MPC) and comparing it to a classical feedback controller, which was designed and implemented on a car for Lane Keeping Assist (LKA) and … …Journal of Mechatronics and Robotics, Vol. 3, Issue 1 · 26 Jun 2019 · 8,019 accessesView PDFCite