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119 results for “Optimization Models”
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Research ArticleOpen accessIn the abstractGrasshopper Optimization Algorithm-Generative Adversarial Network for Lung Cancer Detection and ClassificationSukruth Gowda, A JayachandranLung cancer is one of the most dangerous deadly diseases for individuals worldwide. Thus, the survival rate is low due to the difficulty in detecting lung cancer at advanced stages like symptoms; thus, prominence for early diagnosis is important. The detection and treatment of lung cancer is having great importance for early diagnosis. The existing Convolution Neural Network (CNN) based … …Journal of Computer Science, Vol. 18, Issue 3 · 9 Apr 2022 · 6,575 accessesView PDFCite
Research ArticleOpen accessIn the abstractComputer Users Sitting Posture Classification Using Distinct Feature Points and Small Scale Convolutional Neural Network for Humana Computer Intelligent Interactive System During COVID-19Jheanel Estrada, Larry VeaThe sudden change in our workplace practices from face-to-face work to work from home setup due to the pandemic has brought positive and negative impacts on our overall health. In literature, the use of deep learning and specialized cameras in the estimation of the human pose is popular even if there is a need for high computational resources and complex … …Journal of Computer Science, Vol. 19, Issue 4 · 16 Mar 2023 · 6,553 accessesView PDFCite
Research ArticleOpen accessIn the abstractExperimental and Numerical Analysis of Continuously Coupling Timber-Lightweight EPS Concrete Composite SystemNikola Perković, Vlatka Rajčić, Jure BarbalićA composite system based on concrete and timber represents a very successful engineering solution in the process of optimization of construction. Nowadays, by combining different timber products and concrete classes it is easy to achieve improved engineering features for elements in different static systems or load cases. This paper presents an overview of the research initiated by solving the problem … …International Journal of Structural Glass and Advanced Materials Research, Vol. 5, Issue 1 · 2 Feb 2021 · 6,433 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Classification Model using CNN for Detection of Alzheimer’s DiseaseRagavamsi Davuluri, Ragupathy RengaswamyAlzheimer’s Disease (AD) is commonly called a neurodegenerative disorder and it is a common form of dementia. There is no permanent cure for this brain disease hence the early diagnosis of such disease using medical imaging system is highly significant. Machine learning models play a vital role in the detection of AD. Since most of the conventional machine learning models … …Journal of Computer Science, Vol. 18, Issue 5 · 30 May 2022 · 6,252 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Artificial Neural Network Point Forecasting Models and Prediction Intervals for Solar Irradiance EstimationAntônio Fabrício Guimarães de Sousa, Helaine Cristina Moraes Furtado, Wilson Negrão Macêdo, Anderson Alvarenga de Moura MenesesAn accurate knowledge on solar irradiance prediction is particularly required for proper development and planning of Photovoltaic (PV) energy systems. The main purpose of the present research is to assess the accuracy of Artificial Neural Networks (ANN) short-term forecast of univariate solar irradiance time series, with conventional point prediction and Prediction Intervals (PIs), comparing models. The Lower Upper Bound Estimation … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 17 Jul 2020 · 7,440 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzyNET: A Fuzzy Logic-Based Framework for Enhancing Urban Efficiency in Smart CitiesHemant Kumar, Safdar Tanweer, Parul Agarwal et al.The smart city paradigm emphasizes the strategic use of IoT, Big Data, and digital technologies to optimize urban operations and improve service delivery for citizens. Embedding digital technologies within operational workflows is driven by the objective of improving efficiency and long-term sustainability. The core transformation is Artificial Intelligence (AI) that revolutionizes management of cities through automation and instantaneous decisions based … …Journal of Computer Science, Vol. 22, Issue 7 · 19 Jul 2026 · 820 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing Bias Detection in Tweets Using Bayesian Probabilistic ModelPrasanth G Rao, Harsha Chigurupati, Krish Hashia et al.Content moderation on social media faces persistent challenges from inconsistent evaluation shaped by subjective judgment and subtle semantic variations. This work proposes a Bayesian probabilistic framework for detecting bias in tweets using WordNet-based vocabulary filtering, statistical normalization via z-scores, and threshold optimization. The system is stateless, scalable, and dataset-agnostic, requiring no session-specific information. Unlike complex models such as Support Vector … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,009 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of a Machine Learning Based Mobile and Web Crop Recommendation System for Precision Farming in WardhaAishwarya Kadu, KTV ReddyAgricultural productivity is crucial for economic growth of a nation, especially for countries like India which is highly dependent on agriculture. This study addresses the need for cutting-edge technology to enhance crop productivity by proposing a Mobile/Web-based precision farming system. Leveraging Machine Learning (ML) algorithms, the proposed system recommends optimal crops based on several factors such as environmental parameters (Nitrogen … …Journal of Computer Science, Vol. 22, Issue 3 · 20 Mar 2026 · 1,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,506 accessesView PDFCite