Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

88 results for “gradient method”
Set a search alert
Research ArticleOpen accessIn the keywordsA Practical Approach of Selecting the Edge Detector Parameters to Achieve a Good Edge Map of the Gray ImageAkram A. Moustafa, Ziad A. AlqadiProblem statement: practical approach of detecting edge map was proposed. Approach: The methodology of this approach was presented and tested in order to select the best value of the operator, used to smooth and get the gradient, and the threshold value used to convert the gray gradient to binary edge map, so a practical value of the threshold and edge … …Journal of Computer Science, Vol. 5, Issue 5 · 30 May 2009 · 6,800 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRule Extraction from Radial Basis Functional Neural Networks by Using Particle Swarm OptimizationM. R. Senapati, I. Vijaya, P. K. DashRadial basis functional neural networks (RBFNN) provide an outstanding possibility for generating rules for solving pattern classification problems. One of the most important factors in RBFNN is finding out the center and spread. This paper examines rules extracted from RBF networks trained by Particle swarm Optimization (PSO). The selection of the RBFNN centers, spreads and the network weights can be … …Journal of Computer Science, Vol. 3, Issue 8 · 31 Aug 2007 · 6,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractCoupling Analysis of Thermodynamic Equilibrium of Mass Transfer and Microbial Community Succession in Multiphase System of Dark Tea Solid-State FermentationZhanjun Liu, Jiawei Sun, Taotao Li et al.During the solid-state fermentation of dark tea, the limited material migration, the dynamic evolution of the thermodynamic equilibrium state, and the highly dynamic succession of the microbial community make it difficult to analyze the quality formation mechanism systematically. Traditional research has focused on microbial diversity or sensory quality analysis, lacking a systematic discussion on the regulatory effects of material migration … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,017 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrioritized Experience Replay-Based Deep Deterministic Policy Gradient for Reliable Path Selection in SDN-IoT NetworksGaurav Kumar, G. S. Girisha, N. ShamanthRouting optimization is becoming prominent in Software-Defined Networks (SDN) due to the exponential growth of network traffic demands and the requirement for Quality of Service (QoS). However, reliable routing that satisfies the QoS requirements, such as end-to-end delay, packet loss, and bandwidth, remains a difficult task in SDN. To overcome this limitation, a Deep Reinforcement Learning (DRL)-based Prioritized Experience Replay-based … …Journal of Computer Science, Vol. 22, Issue 8 · 4 Aug 2026 · 1,007 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,351 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnsemble Learning-Based Hybrid Explainable Intrusion Detection System With SMOTE for Enhanced Detection and Interpretability in CybersecurityMohammad Subhi Al-Batah, Taqieddin AldrousWith cyberattacks becoming increasingly sophisticated, there is a growing need for Intrusion Detection Systems (IDS) that are both accurate and interpretable. This study introduces a hybrid IDS framework that integrates Random Forest (RF) and Light Gradient Boosting Machine (LGBM) classifiers with the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance. To enhance transparency and trust, the system also incorporates … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,284 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Prediction Model for Information Anxiety of CSs Based on CMA-ES and XGBoostBin Wang, Li ShaoWith the rapid advancement of information technology, college students are increasingly facing the problem of information overload. Information anxiety, an emerging mental health issue, significantly impacts their studies, daily lives, and mental well-being. Given the limitations of existing methods in handling complex nonlinear relationships and high-dimensional data, this study proposes an efficient and accurate prediction model for college students’ information … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 1 · 21 Apr 2026 · 1,701 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Rainfall Forecasting Using Sequential Momentum-Based Artificial Neural Networks for Urban Flood ManagementSherin K K, G. SuganthiUrban floods cause severe disruption in densely populated cities and damage essential public infrastructure. Rapid urbanization and weak drainage systems further increase the risk during heavy rainfall. Accurate short-term rainfall forecasting is required to support early warning and reduce losses. This research focuses on improving rainfall prediction accuracy using an Artificial Neural Network trained with a new optimizer named Sequential … …Journal of Computer Science, Vol. 22, Issue 4 · 9 Apr 2026 · 1,547 accessesView PDFCite
Research ArticleOpen accessIn the abstractCRISP-DM-Based Mobile Application for Predicting High-Crime Areas in Metropolitan LimaHugo Vega Huerta, Javier Vilca Velasquez, Nicolas Anicama Espinoza et al.The city of Lima, Peru, has been facing a serious climate of citizen security that has risen extremely high in recent years. The objective of this work is to identify and predict areas of high crime incidence through a mobile application based on historical data on criminal incidents recorded by users. The mobile application has been implemented using the CRISP-DM … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,978 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,173 accessesView PDFCite