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419 articles for “model selection”
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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Integrating Plant Selection, Planting Design, and Landscape Construction for Sustainable Site Development
Abstract: This paper explores the interrelationship between plant selection, planting design, and landscape construction in achieving ecologically sustainable and aesthetically pleasing outdoor environments. Plant selection involves choosing species that are well adapted to site conditions, ecological functions, maintenance regimes, and visual preferences. Planting design refers to the arrangement, composition, and spatial organization of plant materials to meet functional, aesthetic, and environmental objectives. Landscape construction encompasses implementation—from site preparation and planting through …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 7–12 Read article
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Emerging Trends in Membrane-Based Gas Separation Technologies
Abstract: Membrane technology has emerged as a groundbreaking solution in various fields, revolutionizing industries such as water treatment, energy production, biomedicine, and environmental protection. Over the past few decades, significant advancements have been made in membrane materials, fabrication techniques, and performance optimization. With the growing global demand for efficient and sustainable separation processes, research has increasingly focused on enhancing membrane permeability, selectivity, and durability to improve performance across various industries, including …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 16–22 Read article
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Detection of Cervical Cancer Using lncRNA Expression Data and Detection of Possible Biomarkers with Bagged CART Machine Learning Method
Abstract: Aim: Cervical cancer (CC), one of the most common gynecological cancers, occurs when the cell layer that forms the surface of the cervix turns into abnormal cells. This type of cancer ranks fourth in cancer-related female deaths, and 3.6% of women living in developed countries suffer from this disease, while approximately 15% of women living in underdeveloped countries are exposed to this cancer. The primary means of reducing the high …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 1, 2023 · pp. 12–20 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Optimization of Mucuna solannie Mud Rheological Parameters
Abstract: The need to optimize rheological parameters by the use of appropriate techniques is the best consideration in drilling mud rheology studies. Various methods are used considering experience on the side of the user, available methods, and flow in pipe or annulus and depending on whether study is done in the field or for research purposes. Mucuna solannie is a legume, and the seed is a viscosifier used in foods in …
Published in Journal of Petroleum Engineering & Technology · Vol. 7, Issue 1, 2017 · pp. 15–26 Read article
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STUDY ON EFFECT OF END MILLING PARAMETERS ON CUTTING FORCES USING RESPONSE SURFACE METHOD
Abstract: Now a day’s research over improvement of surface roughness on mechanical elements has become quite significant in the operational and aesthetical point of view. To enhance accuracy and precision, manufacturing firms are adopting automated systems in order to achieve manufacturing excellence. In the present work the effect of various process parameters like spindle speed, feed and cutting fluid composition on cutting forces in End milling process is investigated by using …
Published in Trends in Mechanical Engineering & Technology · Vol. 8, Issue 2, 2018 · pp. 62–72 Read article
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Harnessing Artificial Intelligence for Precision Physics: A Machine Learning Framework for Data Reconstruction in Support of India's Deep-Tech Missions
Abstract: India's emergence as a global leader in deep-tech innovation is driven by ambitious scientific megaprojects, including the Laser Interferometer Gravitational-Wave Observatory (LIGO)-India, the X-ray Polarimeter Satellite (XPoSat), the Aditya-L1 solar observatory, and the National Quantum Mission (NQM). However, the unprecedented scale and complexity of the observational data generated by these missions present severe computational bottlenecks. Traditional analytical frameworks struggle with non-stationary noise transients, diffusion blurring, and the exponential scaling limits …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 2, 2026 · pp. 48–55 Read article
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A GEO-STATISTICAL MODEL FOR DOWNSCALING SOLAR IRRADIATION DATA: A CASE OF ODISHA
Abstract: Most of the environ-climatic issues are caused by the over-burning of fossil fuels such as coal and petroleum. Our over-dependency on non-renewable resources has led us to over-exploitation of fossil Fuels. Sustainable development has become one of the causes of the growing demand for clean energy. With the current development of new technology, the efficiency of solar panels has increased severalfold. So, identifying the energy resources properly is the most …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 13, Issue 3, 2023 · pp. 12–17 Read article
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Exploring the Influence of Machining Parameters on Geometric Form and Orientation Controls (23 Design)
Abstract: This work explores the influence of machining parameters using on geometric form controls flatness and straightness as well as orientation control parallelism using an aluminum 6061 workpiece. Due to its good strength, machinability and cost- effectiveness, aluminum 6061 is widely used. In this experimental work, full factorial design is used and each factor has two levels. The response parameters chosen include flatness, straightness, and parallelism, which govern the form and …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 1, 2025 · pp. 10–16 Read article
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Modelling of An Electric Tractor Powertrain using MATLAB/Simulink
Abstract: Lithium-ion battery pack technology is the current trend in the automotive industry. For this study, the authors have selected NMC 18650 lithium-ion cells to design a battery pack for electric tractors and simulating the electric tractor powertrain model to gauge and size the battery pack configuration parameters. The tractor parameters have been selected by comparing with some Indian and Japanese electric tractors. The simulation has been carried out using MATLAB/Simulink …
Published in Journal of Experimental & Applied Mechanics · Vol. 12, Issue 2, 2021 · pp. 1–14 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
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Analysis of Crashworthiness of a Saloon Car Fitted with CNG Cylinder
Abstract: There is an increase in demand for compressed natural gas vehicles in India. Due to the high gasoline prices and lack of electric vehicle infrastructure in India, compressed natural gas vehicles are the only feasible option. This research work focuses on the crashworthiness of a saloon car fitted with a compressed natural gas cylinder under rear-collision conditions. Four different candidate materials of the same thickness are chosen for the cylinder …
Published in Journal of Polymer & Composites Read article
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3D-Printed Polymeric Drug Delivery Systems for Personalized Medicine
Abstract: Personalized medicine has revolutionized healthcare by tailoring treatments to individual patient needs. Among the emerging technologies, 3D printing has demonstrated immense potential in fabricating polymeric drug delivery systems with precise control over drug release, dosage, and bioavailability. These systems offer customized therapeutic solutions, improving efficacy while reducing adverse effects. This paper provides an overview of 3D-printed polymeric drug delivery systems, discussing the types of polymers used, fabrication techniques, applications in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 313–325 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article