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544 articles for “predictive algorithm”
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture
Abstract: Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture" explores the convergence of cutting-edge technologies in revolutionizing traditional farming practices towards sustainability. This study investigates the integration of Internet of Things (IoT), Artificial Intelligence (AI), and Image Processing techniques in agricultural contexts, aiming to enhance efficiency, productivity, and environmental stewardship. Through a comprehensive review of recent advancements and case studies, this research elucidates the transformative potential of IoT-enabled …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 52–69 Read article
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A Review of Code Defect Likelihood Using ML Methods
Abstract: AbstractSoftware begets defects and defects are inevitable in software design and coding. This paper focused on five machine learning analysis models (MLAM); Support Vector Machine, Random Forest, K-Nearest Neighbor, Classification and Regression Tree, and Linear Discriminant Analysis. These models are trained to detect software defects using the software defect dataset from Promise data repository. The collected dataset is preprocessed to reduce the amount of redundant features using a dimension reduction …
Published in Journal of Open Source Developments · Vol. 7, Issue 3, 2020 · pp. 1–6 Read article
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Early Heart Disease Prediction Using Hybrid Machine Learning Techniques
Abstract: In the contemporary era, cardiovascular disease is one in all the most causes of death within the world. Estimating Heart problems i.e cardiopathy is a crucial challenge within the area of clinical data analysis. Large volumes of data produced by the healthcare sector have been proved to be useful for helping with decision-making and speculation, thanks to machine learning (ML).. Various studies help us to review and supply glimpse into …
Published in Journal of Microcontroller Engineering and Applications · Vol. 9, Issue 2, 2022 · pp. 35–41 Read article
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An Explanatory Theory of Predictive Analysis and Industry 5.0 for Students
Abstract: The incorporation of cutting-edge technologies like artificial intelligence, the Internet of Things (IoT), and robotics into manufacturing operations has given rise to Industry 5.0, often referred to as the "Smart Factory". This fresh approach to manufacturing holds the potential to enhance efficiency, lower expenses, and enhance overall operational effectiveness. Predictive analysis is the key technology that enables Industry 5.0 to achieve these goals by utilizing data and machine learning algorithms …
Published in Journal of Communication Engineering & Systems · Vol. 13, Issue 2, 2023 · pp. 8–12 Read article
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Enhancing Cybercrime Detection Through Big Data Analytics: A Conceptual Framework
Abstract: The growing complexity of cybercrime reduction and prevention difficulties necessitates a different approach to dealing with the massive amounts of data involved. The issues of reducing and preventing cybercrime are becoming more complex as cybercrime becomes ingrained in our daily lives. When it comes to showcasing the original division of criminal activities, traditional police operations typically fall short, which means they contribute less to the right deployment of police resources. …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 1–11 Read article
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Predicting Employees Performance using Data Mining Techniques
Abstract: Human resources management (HRM) has become one of the essential interests of managers and 4decision-makers in almost all types of businesses to adopt plans for correctly discovering highly qualified employees. In this research, data mining techniques were utilized to build a classification model for predicting the performance of employees using a real dataset. For this, we are using different methods such as support vector machine, Logistic Regression and Neural Network. …
Published in Recent Trends in Parallel Computing · Vol. 8, Issue 1, 2021 · pp. 4–13 Read article
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An Enhanced Application Oriented Predictive Analytic using Optimal Deep Learning Model
Abstract: In order to presents better Predictiveanalytic models of different data using various machine learning algorithms. The data prediction is developed on various applications. These applications are facing many challenges while collecting data and data selection etc. The proposed prediction model involves several phases like (a) Data acquisition, (b) Data cleaning, (c) Data normalization, (d) Optimal Feature selection, and (e) Prediction. The optimal feature selection will be accomplished by a new …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 7, Issue 2, 2020 · pp. 5–10 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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Drug Discovery and Design: Focus on computational approaches used in the discovery and design of new drugs
Abstract: Computational approaches have revolutionized the field of drug discovery and design, offering efficient and cost-effective strategies for identifying and developing new therapeutics. This review article explores the application of computational methods in drug discovery, with a focus on virtual screening techniques, molecular docking, molecular dynamics simulations, and quantitative structure-activity relationship (QSAR) models. Virtual screening plays a crucial role in narrowing down large chemical libraries by utilizing ligand-based and structure-based approaches. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 1, 2023 · pp. 26–30 Read article
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Smart Weather Monitoring System Using ESP32 and IoT
Abstract: The increasing unpredictability of climate conditions necessitates an efficient and real-time weather monitoring system. The following paper describes an IoT weather monitoring system using the ESP32 microcontroller, connected to various environmental sensors to gather and process atmospheric information. The system uses a DHT11 sensor to measure temperature and humidity, an MQ135 gas sensor for measuring air quality, and a PM2.5 sensor to measure the level of particulate matter. The ESP32 …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 2, 2025 · pp. 25–36 Read article
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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 21–29 Read article
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Enhancing Online Security: Machine Learning Methods for Phishing Detection—Literature Survey
Abstract: Phishing attacks represent a substantial online security threat as they mimic authentic websites to trick users into disclosing sensitive information. Detecting these malicious websites is crucial for safeguarding user data and maintaining digital trust. This summary provides insight into the application of machine learning methods in the identification of phishing websites. Machine learning, which falls under the umbrella of artificial intelligence, has proven to be a robust instrument for automating …
Published in Journal of Web Engineering & Technology · Vol. 10, Issue 3, 2023 · pp. 29–34 Read article
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Precision Medicine for Neurofibromatosis Type 1: Progress and Prospects in Drug Discovery
Abstract: Objective: The development of neurofibromas, café-au-lait spots, and other neurological problems are the hallmarks of neurofibromatosis type 1 (NF1), a hereditary disorder. The dearth of efficacious pharmaceutical therapies underscores the need for novel therapeutic approaches, even in the face of clinical variability. Through very accurate prediction of the binding affinity of possible therapeutic drugs with the target protein, the computational technique known as “molecular docking” has become a potent tool …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 01–15 Read article
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Enhancing Energy Efficiency in Air Handling Units Through AI Driven Optimization
Abstract: This research explores the implementation of artificial intelligence (AI) in enhancing the energy efficiency of Air Handling Units (AHUs) in manufacturing facilities. The study proposes a comprehensive solution architecture that incorporates temperature and humidity sensors within AHUs, utilizing RS485 for data communication. The collected data undergoes exploratory analysis, which informs the training of a decision tree algorithm, chosen for its accuracy and compatibility with edge gateways. The algorithm's predictions enable …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 2, 2024 · pp. 19–28 Read article
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Smart Shuttle System: An IoT and Machine Learning Based Approach
Abstract: The Smart Shuttle System is an IoT-based system designed to provide a hassle-free, cashless payment experience for students using the shuttle service. The system utilizes RFID (Radio Frequency Identification) technology to identify students and deduct the fare amount from their account. Radio Frequency Identification (RFID) technology is being considered as an alternative to traditional money and Unified Payments Interface (UPI) for making payments due to several advantages it provides over …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 9–22 Read article
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Design and Development of Agrobot Using Feed Forward Network for Smart Farming Agriculture
Abstract: The Agrobot framework is a form of natural language processing that requires training to understand human language and meet user needs accordingly. The development of a chatbot tailored for the agricultural industry represents a significant advancement in agricultural technology. This chatbot serves as an interactive tool to assist farmers in various aspects of agricultural practices, including crop management, pest control, weather forecasting, and market information. The main objective of this …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 1, 2024 · pp. 6–14 Read article
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Navigating Risk-Based Approaches in Quality Assurance: Strategies, Implementation, and Impact
Abstract: This review investigates the implementation of a risk-based approach within Quality Management Systems (QMS) as stipulated by ISO 9001:2015 regulations. It scrutinizes the challenges organizations encounter when transitioning to ISO 9001-2015 requirements, particularly focusing on the alignment of conceptual frameworks and processes among stakeholders. A key objective of this review is to propose a refined definition of "quality risk" and "risk-based thinking in QMS" to address the idiosyncratic characteristics of …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 2, 2024 Read article
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Artificial Intelligence in Smart Dairy Farming (SDF)
Abstract: Due to increasing demand for quality of milk in dairy farming also for the sustainability, productivity and maintenance of good health of animals. various challenges are faced by dairy farmers and can be addressed using Artificial Intelligence technologies ,By using AI here the individual health ,behavior ,feed management robotic milking and stress free milking system will be implemented .AI technologic implementation will frame the Smart dairy farming in properly and …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 16–20 Read article