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119 results for “Optimization Models”
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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 · 1,667 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 · 1,512 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 · 6,258 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluating Patient Readmission Risk: A Predictive Analytics ApproachAvishek Choudhury, Dr. Christopher M. GreeneWith the emergence of the Hospital Readmission Reduction Program of the Center for Medicare and Medicaid Services on October 1, 2012, forecasting unplanned patient readmission risk became crucial to the healthcare domain. There are tangible works in the literature emphasizing on developing readmission risk prediction models; However, the models are not accurate enough to be deployed in an actual clinical … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 4 · 7 Dec 2018 · 8,161 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,520 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvanced Hierarchical Deep Learning Approach for Intrusion Detection: Hyperparameter Tuning and Performance Evaluation on the CICIDS DatasetAjeet Singh, Azath M, Shahazad Niwazi Qurashi et al.Intrusion Detection Systems (IDS) are essential in the communication security and integrity of contemporary network architectures. This study introduces a novel advanced hierarchical deep learning model for network intrusion detection using the CICIDS dataset-2019. To improve the detection accuracy, the proposed model architecture builds several deep learning layers embedded with hyperparameters' optimization. Additional preprocessing steps, including over-sampling and min-max scaling, … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,158 accessesView PDFCite
Research ArticleOpen accessIn the abstractChilled Water VAV System Optimization and Modeling Using Artificial Neural NetworksRand Talib, Nabil Nassif, Maya Arida, Taher Abu-LebdehIn 2016, It was estimated that about 40% of total U.S. energy consumption was consumed by the residential and commercial sectors. According to EIA, in 2009, the energy consumption in U.S. homes was 48% which was down from 58% in 1993 (Residential Energy Consumption Survey (RECS). The development of building energy savings methods and models becomes apparently more necessary for … …Energy Research Journal, Vol. 9, Issue 1 · 6 Feb 2019 · 6,452 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-Objective Optimization of FRP Jackets for Improving the Seismic Response of Reinforced Concrete FramesCorrado Chisari, Chiara BedonIn this study, a multi-objective Genetic Algorithm (GA) optimization procedure is proposed for the seismic retrofitting of Reinforced Concrete (RC) building frames via Fiber-Reinforced Polymer (FRP) jackets. The optimization problem is solved via numerically efficient but accurate Finite-Element (FE) models able to take into account the strengthening and ductility increase contribution for a given FRP jacketing configuration. Based on a … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 3 · 27 Sep 2016 · 8,832 accessesView PDFCite
Research ArticleOpen accessIn the abstractA ROBUST OPTIMIZATION APPROACH FOR INDEX TRACKING PROBLEMMohsen Gharakhani, Forough Zarea Fazlelahi, S. J. SadjadiIndex tracking is an investment approach where the primary objective is to keep portfolio return as close as possible to a target index without purchasing all index components. The main purpose is to minimize the tracking error between the returns of the selected portfolio and a benchmark. In this study, quadratic as well as linear models are presented for minimizing … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Dec 2014 · 8,878 accessesView PDFCite
Research ArticleOpen accessIn the abstractA MATHEMATICAL ANALYSIS OF THE INCLUSION OF INSTITUTIONAL BETTING FUNDS INTO STOCK MARKET: THE CASE OF TECHNICAL AND FUNDAMENTAL PAYOFF MODELS IN HORSERACE BETTINGCraig George Leslie Hopf, Gurudeo Anand TularamHorserace win and place returns have yet to be considered seriously as portfolio inputs in financial trading markets. However there exist technical and fundamental stochastic models of parametric and nonparametric distribution that appear to optimize expected returns from win and place investing in the horserace wagering market. In this study, a complex number optimization technique is introduced and applied to … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 23 Aug 2014 · 6,794 accessesView PDFCite