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260 articles for “Model Selection”
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article
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A Study on Site Selection Component of Model Logistics Park: A Case of Uttar Pradesh, India
Abstract: Uttar Pradesh, India’s 4th largest state and 3rd largest economy eyeing being a One trillion-dollar economy. Among the top 5 manufacturing states of India, home to the second-highest number of Micro, Small, and Medium Enterprises (organized and unorganized) in India. The National Highways Logistics Management Limited under the Ministry of Road Transport and Highways (MoRTH) and the National Highways Authority of India proposed Multi-Modal Logistics Parks (MMLPs) as an initiative …
Published in Trends in Transport Engineering and Applications Read article
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Lipid Oxidation, Maillard Reaction, and Their Possible Interrelation in Selected Foods and Model Systems – A Review
Abstract: The present article highlights on the medicinal value of leeches. Leech belongs to phylum Annelida have played a significant role in ancient medicine for centuries, with their therapeutic and medicinal applications dating back to ancient human civilizations such as those of Egypt, Greece, and India. Historically, incidences shows it associated with blood letting, leeches were believed to restore balance to the body’s humors. In recent times, new experiments are being …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–15 Read article
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User Review-Driven Recommendation Model for E-Scooter Selection
Abstract: In the era of rising environmental awareness and the growing emphasis on sustainable mobility practices, electric scooters (e-scooters) have gained significant popularity as an efficient and eco-friendly alternative to conventional modes of transport. Their ability to reduce carbon emissions, minimize traffic congestion, and offer cost-effective commuting solutions has made them highly attractive, particularly in urban environments. However, with the rapid expansion of the e-scooter market, consumers are faced with an …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 6–16 Read article
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Comparative Analyses of Select Microbial Growth Inhibited Rate Models
Abstract: Food waste is a complex substrate comprising of different mixtures of chemical compounds. The growth rate of micro-organism in such environment will experience inhibition. Consequently, the Monod’s model will not be able to describe the growth rate of its bacteria. The Aiba’s, Andrews and the Haldane’s growth rate models that are accounts for growth rate of bacteria with inhibition were compared. To do this, seven different batch experimentations; each with …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 15, Issue 1, 2024 · pp. 16–24 Read article
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To Evaluate the Performance of the Selected Hybrid Systems and Validation of Mathematical Model with the Experimental Data
Abstract: The main aim of this paper to evaluate the performance of the PV-Wind hybrid systems and validation of mathematical model with the experimental model. In the research paper, the experimental model of PV-Wind Hybrid system has been installed at a height of 22 meters in the School of Energy and Environmental studies, DAVV, Indore, and M.P., India. The theoretical calculation of the wind generator output has also been compared with …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 2, 2025 · pp. 20–28 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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Traffic Detection Algorithms Analysis using ML
Abstract: It is difficult to watch traffic on crowded roads. Traffic monitoring procedures are time-consuming, expensive, labor-intensive, and require human operators. The limited accessibility hindered the storing and processing of large-scale video streams. Nonetheless, it is now possible to employe video feeds from traffic monitoring systems for number plate recognition, object tracking, traffic behavior analysis, and surveillance. Static image recognition and vehicle identification in a traffic surveillance system are very useful …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Machine Learning Innovations for Effective Spam Comment Filtering in Social Networks
Abstract: The increasing prevalence of social media platforms has revolutionized communication, fostering unparalleled levels of connectivity and data exchange. However, the widespread increase in spam comments presents a serious threat to the integrity of online discussions, potentially undermining the quality of interactions. To confront this issue, our proposed model utilizes machine learning techniques to bolster spam comment detection across various social media platforms. This endeavor involves a thorough investigation encompassing data …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 19–24 Read article
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Zebra Fish Embryo Assay: A Wonderful Tool for Ecotoxicological Risk Assessment with Special Reference to Heavy Metals - An Overview
Abstract: In recent years, environmental pollution has become a pressing concern, prompting extensive research in aquatic ecotoxicology. With environmental degradation getting worse day by day, ecotoxicology research has gained a lot of attention. This area of study examines how biological communities in aquatic environments are affected by environmental contaminants. To unravel the toxicological mechanisms of these exogenous compounds, scientists turn to biological models. Several aquatic species, including zebrafish, toads, and big …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 2, 2025 · pp. 56–70 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Cost Model of Acquisition and Merger in Construction Industry
Abstract: Merger and Acquisition in India is at an all-time high with more buyers now than before; it has been accounting for 80% of closed deals in 2020–2021, up from 70% in 2017–2019. To determine the Merger and Acquisition of the company, this article explores the main factors in the Merger and Acquisition process. And also study the main framework of the Merger and Acquisition. And, also, the article discusses the …
Published in International Journal of Architectural Design and Planning Read article
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Comparative Analysis of Kinetic Models for Simulation of Biogas Production from Cow Dung and Fruit Waste via Anaerobic Digestion
Abstract: This study investigates the optimization of biogas and biofertilizer production from cow dung and fruit waste through anaerobic digestion, utilizing various microbial growth kinetic models. Simulations were conducted using the Monod, Moser, Contois, and Tessier models to predict biogas yield and assess model accuracy. Results indicated that the Tessier model provided the closest fit to experimental data, with a biogas yield of 0.45 m³/kg VS, while the Monod model overestimated …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 47–63 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article