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77 articles for “random forest classification”
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Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article
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AIS-based Anomaly Detection for IUU Fishing Activities
Abstract: The future of the Earth’s fish businesses is seriously threatened by the continuous use of illegal or illicit, unreported, and unregulated (IUU) fishing methods, a growing global demand, and deteriorating ocean ecosystem health. The livelihoods of legal fishing are also harmed by IUU fishing. The ongoing efforts to develop sustainable fisheries policies are also hampered by this. In order to manage fishery resources and ensure the safety of maritime traffic, …
Published in Current Trends in Information Technology · Vol. 13, Issue 1, 2023 · pp. 22–36 Read article
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Sentiment Analysis of Twitter Data for Better Services of Airlines Using Classifier-Model Algorithms, AI, and NLP Techniques
Abstract: The rising attractiveness of social media sites and usage of social websites is to share information. Tweet, for instance, is a stage in which audiences direct, and examine posts recognized as “tweets,” and engage together in one-of-a-kind communities through feedback, comments, tweets, and reviews. There are so many companies that want tweets, comments, reviews, and analyses on their products and services, so they can improve their services, products, and customer …
Published in Current Trends in Information Technology · Vol. 12, Issue 3, 2022 · pp. 29–46 Read article
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Fusion of deep learning autoencoders with random forest for wetland classification using Sentinel-2A data: A case study on Sirpur wetland
Abstract: Present study analyses the performance of deep leaning algorithm-autoencoder to reduce data dimension as compared to conventional models. Classification accuracies of Sirpur wetland using Sentinel 2A dataset with different inputs have also been studied. These inputs sets comprise the reconstructed data through compression of original 13 bands into 4 bands using decoder algorithm, first four Principal Components, all spectral bands, and spectral indices. Random Forest classifier (RF) is used to …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 25–35 Read article
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Optimizing Sentiment Analysis with Naïve Bayes and Random Forest Techniques: A Result-based Approach
Abstract: In the increased digitalization, the sentiment analysis and classification have evolved as an eminent area to determine the polarity of positive, negative, and neutral reviews of the customers and users on products. It is an integral application field that employs supervised learning, Machine Learning, and Natural Language Processing concepts. The proposed Semantic Analysis and Classification using Naive Bayes and Random Forest system accomplishes the sentiment polarity by classifying the user …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 46–57 Read article
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Comparative Study of Classifiers for Monitoring Fake Reviews of Online Products Using Opinion Mining
Abstract: With the increasing popularity of e-commerce, online dealers seek reviews or opinions from customers regarding the quality and service of their sold products. As the number of customer reviews grows rapidly, potential buyers face difficulties in reading and assessing them to make informed decisions. Unfortunately, some review websites include fake positive reviews, either added by the product companies themselves or submitted by users who have not made a purchase. This …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 52–59 Read article
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Disease Prediction for Heart using Data Mining Techniques and Decision Tree Classification
Abstract: Heart disease is a prominent cause of death worldwide, and many people are concerned about it. Early detection of heart disease becomes very crucial and has the potential to save many lives. However, detecting cardiovascular diseases such as heart attacks, coronary artery disease, and others of similar types is a critical challenge presented by routine clinical data analysis, even by using well known algorithms. We can’t risk lives of people …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 16–22 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Liver Patient Analysis Using Machine Learning
Abstract: Liver, a critical inside organ of the human body whose chief errands are to take out created squander delivered by our life form, digest food, and safeguard nutrients and energy materials. The liver problem can cause different deadly infections, including liver malignant growth. Early conclusion, and treating the patients are necessary to diminish the gamble of those deadly sicknesses. As the finding of liver illness is costly and refined, various …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 29–35 Read article
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Human Activity Recognition Using For Smartphone Sensors To Predict The Best Accuracy Based On Machine Learning Algorithms
Abstract: Human activity recognition requires predicting the action of a person based on sensor-generated data. Due to the enormous number of applications possible by modern ubiquitous computing devices, it has sparked a lot of attention in recent years. It categorizes data into actions such as walking, sitting, standing, and lying. The accelerometer and gyroscope were used to generate the sensor data, and the sensor signals were pre-processed with noise filters. The …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 1, 2022 · pp. 12–23 Read article
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DISEASE PREDICTION SYSTEM USING MACHINE LEARNING
Abstract: Machine learning (ML) is a rising field. It already plays an important role in many fields, with projects of all sizes showing its positive impact. One such use of machine learning algorithms is in the healthcare field. Medical facilities need to be improved in order to make better decisions about patient diagnosis and treatment options. In this paper, we attempt to use the performance of Machine learning equipment in health …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 2, 2021 · pp. 14–18 Read article
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Climate Change Including Forest Fire Prediction using Machine Learning and Deep Learning
Abstract: Climate change alludes to long haul shifts in temperatures and atmospheric conditions. These movements might be regular, for example, through varieties in the sun-oriented cycle. In any case, since the 1800s, human exercises have been the fundamental driver of climate change, basically because of consuming fossil fuels like coal, oil and gas. Many individuals think climate change mostly implies hotter temperatures. Be that as it may, the temperature climb is …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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FutureGen – Predicting Genetic Health
Abstract: FutureGen is an intelligent web-based system developed to help couples assess the risk of genetic disorders in their future child through data-driven analysis. The system brings together modern web technologies and machine learning to offer accurate and accessible predictions. The frontend, built with React, provides an intuitive interface for user interaction, while a Flask-based backend API handles model inference and manages communication with the Supabase database, which securely stores user …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article
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Data-Driven Machine Learning Approach for Vehicle Fuel Economy Prediction and Performance Monitoring Using Real-World OBD Data
Abstract: Modern passenger vehicles generate large volumes of operational data through On-Board Diagnostics (OBD) systems, enabling continuous observation of vehicle performance under real-world driving conditions. However, much of the existing research mainly analyses previously recorded data and does not provide predictive mechanisms for monitoring vehicle performance under dynamically varying operating conditions. This study presents an AI and machine learning–based method for predicting and monitoring real-world vehicle performance and fuel economy using …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 47–66 Read article