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552 articles for “intelligent modeling”
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A Quantitative Fuzzy MCDM Framework for Decision Support in Uncertain Environments
Abstract: Fuzzy mathematics play an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and it signs other possible solutions in addition to fuzzy mathematics. Fuzzy models offer a versatile and precise approach to assessing complex situations through the use of fuzzy sets, membership functions, and aggregation methods. Through time, cost and quality, the project management case study illustrates how fuzzy logic works for them. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 1–8 Read article
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Swarm Intelligence in Software Engineering: A Systematic Review of Crowd-Based Development Models
Abstract: The crowd-based software production model has emerged as a transformative paradigm, leveraging global collaboration, decentralized governance, and artificial intelligence (AI)-driven automation to develop software efficiently. Traditional software development models, characterized by centralized control and in-house teams, are increasingly giving way to distributed, community-driven efforts. Key advancements such as blockchain-based decentralized autonomous organizations (DAOs), AI-assisted coding and debugging, and edge computing applications are reshaping the landscape of software engineering. DAOs provide …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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Controlling Media Player Through Hand Gesture Recognition System Using CNN and RNN Models
Abstract: Artificial intelligence markup language (AIML) project represents a pioneering endeavor in the realm of media player control through hand gesture recognition, merging advanced technologies like convolutional neural networks (CNN) and recurrent neural networks (RNN). By harnessing the image analysis capabilities of CNN, our system ensures accurate, real-time detection, and interpretation of intricate hand gestures, enabling users to interact with their media content naturally and seamlessly. What sets our project apart …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 29–34 Read article
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A Comparative Study of different Techniques to predict Maternal Morbidity and Mortality Model
Abstract: Artificial intelligence (AI) encompasses a range of techniques, including machine learning and deep learning, which are increasingly utilized in the healthcare sector for tasks such as disease diagnosis and drug discovery. To achieve accurate disease diagnosis through AI, it is essential to integrate data from multiple medical sources, including ultrasound imaging, magnetic resonance imaging (MRI), mammography, genomics, and computed tomography (CT) scans, among others. This article presents a comprehensive review …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 Read article
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Unveiling Fairness: A Quest for Ethical Artificial Intelligence and Bias Mitigation
Abstract: Artificial intelligence (AI) systems have become ubiquitous across areas like finance, healthcare, employment, and criminal justice. However, they suffer from issues of unfair bias, lack of transparency, and broad ethical implications impacting vulnerable societal groups disproportionately. This paper reviews key challenges around AI ethics and bias while proposing data-driven guidelines mitigating such algorithmic harms through rigorous statistical testing, predictive modeling ensembles adjusting distortion vectors and AI audits by domain experts …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 28–31 Read article
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Modern Computer-aided Drug Design Methods: A Review
Abstract: Computer-aided drug design (CADD) has emerged as a crucial tool in the drug discovery process, offering a time-efficient and cost-effective approach to identifying potential drug candidates. This review aims to provide an overview of modern CADD methods, including high-throughput screening (HTS), structure-based drug design (SBDD), ligand-based drug design (LBDD), structure-based virtual screening (SBVS), and ligand-based virtual screening (LBVS). We discuss the basic principles, applicability, and limitations of each method, highlighting …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 2, 2024 · pp. 14–20 Read article
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Student Academic Achievement Forecast Based on Emotional Intelligence, Personality, Demographic Characteristics and Attitude Towards Education and Future Career
Abstract: This study was aimed at predicting students' academic achievement based on emotional intelligence of personality traits, attitudes to education and future career. The present study was a correlational-analytical study. The statistical population of Zanjan University students in the academic year of 1395-1395 was the sample of 489 people selected by cluster random sampling method. Academic Resilience Scale (ARI) and Schotte Emotional Intelligence Questionnaire and Researcher Attitude Questionnaire were used to …
Published in International Journal of Education Sciences · Vol. 1, Issue 2, 2024 · pp. 25–36 Read article
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Utilizing Artificial Intelligence and Remote Sensing to Predict Flooding in Real-Time and Address Climate Resilience Policy in South Asia
Abstract: South Asia, a region characterized by hydro-climatic instability, faces an intensifying risk from devastating flooding, aggravated by human-induced climate change and intricate river basin interactions. Traditional flood prediction systems, based on limited in-situ data and resource-intensive physical models, have serious delays and resolution problems that make it harder to reduce disaster risk. The combined applications of Artificial Intelligence (AI) and high-resolution remote sensing (RS) constitute a paradigm shift in real-time …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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A Detailed Review on Intelligent and Robust Control Strategies for Autonomous Underwater Vehicles with Emphasis on Navigation, Path Tracking, and Stability Enhancement
Abstract: Autonomous Underwater Vehicles (AUVs) have gained significant attention due to their applications in ocean exploration, underwater surveillance, environmental monitoring, and offshore industries. The control of AUVs presents various challenges due to the highly dynamic and uncertain underwater environment, nonlinear hydrodynamics, and external disturbances. This review paper explores various control strategies employed for AUVs, including classical control methods such as Proportional-Integral-Derivative (PID) controllers, modern techniques like Model Predictive Control (MPC), and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 28–52 Read article
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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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A Review of Drug Design Techniques Assisted by Computers to Combat Diabetes
Abstract: Diabetes mellitus is a global health concern characterized by chronic hyperglycemia and associated complications. The creation of innovative medicines with enhanced efficacy and safety profiles continues to be a top focus, notwithstanding improvements in treatment. A useful method in drug development, computer-aided drug design (CADD) makes it easier to identify possible therapeutic candidates and optimise lead molecules. An extensive synopsis of CADD tactics used in the fight against diabetes is …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 1, 2025 · pp. 1–10 Read article
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Physics-Informed Generative and Tensor-Based Framework for DNA Sequence Simulation and Genomic Structure Discovery
Abstract: In this paper, we explore the intersection of artificial intelligence (AI) and mathematical physics to propose advanced methods for DNA sequence generation and analysis. Specifically, we investigate how physics-informed Generative Adversarial Networks (GANs) and tensor network representations can be harnessed to restructure DNA for applications in genetic science. The proposed methodology offers a unique integration of concepts of thermodynamic modeling with innovative GAN architecture in order to allow the creation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Mario Ai Model Using Gaming Reinforcement Learning
Abstract: It is essential for research on computational and/or artificial intelligence (CI/AI) applied to games to have relevant games to apply AI algorithms to. This is pertinent. It doesn't matter if one is studying how to use CI/AI techniques to test and improve AI (e.g., games provide challenging yet scalable problems which engage many central aspects of human cognitive capacity) or how to use CI/AI techniques to improve games (e.g., player …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 · pp. 1–6 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
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A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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AI For Climate Vulnerability Assessment
Abstract: Climate change is one of the biggest problems we face every day. The main problems are high temperatures, rising sea levels, and changes in weather, which will be worse in the upcoming years. To predict and adapt to these impacts, we need to create data-driven solutions. The main tool for predicting climate change was artificial intelligence, which can also be utilised to predict the weather and alert people of impending …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 18–33 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article
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Artificial Intelligence in Cybersecurity: Emerging Trends, Technological Advancements, and Future Directions for Cyber Defense
Abstract: Artificial Intelligence (AI) is revolutionizing the field of cybersecurity by automating complex security tasks, improving threat detection capabilities, and enhancing the precision of threat response mechanisms. With the rapid evolution of cyber threats such as malware, ransomware, phishing, and data breaches, conventional security systems are often insufficient to provide timely and accurate protection. AI, powered by machine learning algorithms and neural networks, enables the analysis of vast datasets to detect …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 103–112 Read article
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AI Chatbot for Expressing Visual Content
Abstract: Recently, the artificial intelligence (AI) chatbot for expressing visual content has shown remarkable multi-modal capabilities. It can recognize funny features in photos and create webpages straight from handwritten text. These characteristics are uncommon in earlier vision language models. We think the use of a more sophisticated large language model (LLM) is the main factor behind vision verbalizer's superior multi-modal generating capabilities. We introduce vision verbalizer, which employs a single projection …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 11–19 Read article