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139 results for “Training Algorithm”

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Research ArticleOpen accessIn the abstractEnergy and Carbon Flux Coupling: Multi-ecosystem Comparisons Using Artificial Neural NetworkAssefa M. Melesse, Rodney S. HanleyA multi-ecosystems carbon flux simulation from energy fluxes is presented. A new statistical learning technique based on Artificial Neural Network (ANN) back propagation algorithm and multi-layer perceptron architecture was used in the CO2 simulation. Four input layers (net radiation, soil heat flux, sensible and latent heat flux) were used for training (calibration) and testing (verification) of model outputs. The 15-days … …American Journal of Applied Sciences, Vol. 2, Issue 2 · 28 Feb 2005 · 7,347 accessesView PDFCite
Research ArticleOpen accessIn the abstractChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 651 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Machine Learning-Based Sentiment Analysis of Article 370 Tweets to Support Government Policy DecisionsSubhasis Mohapatra, Sudhir Kumar Mohapatra, Sweta Samantaray et al.This study proposes a robust sentiment analysis framework to evaluate public opinion on the abrogation of Article 370 using Twitter data. The methodology begins with tweet collection through the Twitter API, followed by systematic preprocessing. Sentiment labels were generated using the Text Blob lexicon-based polarity scoring approach to facilitate the construction of a large-scale sentiment dataset. Features are extracted, and … …Journal of Computer Science, Vol. 22, Issue 6 · 2 Jul 2026 · 914 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent System for Cardiovascular Disease Prediction Using Deep LearningDeepika Arora, Deepak Dudeja, B K AgrawalHeart disease remains among the major causes of death in the world. Hence, accurate and reliable prediction schemes are key. To detect the presence of diseases in early stages, data mining and deep learning algorithms offer powerful tools to determine important trends in large and complex data. To enhance the prediction of cardiac diseases, this paper proposes a hybrid deep … …Journal of Computer Science, Vol. 22, Issue 2 · 9 Mar 2026 · 1,607 accessesView PDFCite
Research ArticleOpen accessIn the abstractA STING Algorithm and Multi-dimensional Vectors Used for English Sentiment Classification in a Distributed SystemVo Ngoc Phu, Vo Thi Ngoc TranSentiment classification is significant in everyday life, such as in political activities, commodity production and commercial activities. Finding a fast, highly accurate solution to classify emotion has been a challenge for scientists. In this research, we have proposed a new model for Big Data sentiment classification in the parallel network environment - a Cloudera system with Hadoop Map (M) and … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 1 · 22 Dec 2017 · 7,594 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest and Extreme Gradient Boosting with Bayesian Hyperparameter Optimization for Landslide Susceptibility Mapping in Penang Island, MalaysiaDorothy Anak Martin Atok, Soo See Chai, Kok Luong Goh et al.Landslide susceptibility models often face challenges of overfitting and overestimation. This research focuses on improving the predictive capabilities of the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms by applying Bayesian Hyperparameter Optimization (BayesOpt). Penang Island, a region in Malaysia prone to frequent landslides, was chosen as the study area. Ten Landslide Conditioning Factors (LCFs), including elevation, slope angle, … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 3,103 accessesView PDFCite
Research ArticleOpen accessIn the abstractTHE CLINICAL APPLICATIONS FOR AUTOMATIC DETECTION OF EXUDATESK. Wisaeng, N. Hiransakolwong, E. PothirukNowadays, the retinal imaging technology has been widely used for segmenting and detecting the exudates in diabetic retinopathy patients. Unfortunately, the retinal images in Thailand are poor-quality images. Therefore, detecting of exudates in a large number by screening programs, are very expensive in professional time and may cause human error. In this study, the clinical applications for detection of exudates … …American Journal of Applied Sciences, Vol. 11, Issue 10 · 27 Sep 2014 · 6,446 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Face Recognition in Video by Bit Planes SlicingM. Jasmine Pemeena Priyadarsini, K. Murugesan, Srinivasa Rao Inbathini, Visal KumarProblem statement: Video-based face recognition must be able to overcome the imaging interference such as pose and illumination. Approach: A model is designed to study for face recognition based on video sequence and also test image. In training stage, single frontal image is taken as a input to the recognition system. A new virtual image is generated using bit plane … …Journal of Computer Science, Vol. 8, Issue 1 · 26 Oct 2011 · 7,420 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Efficient Implementation of Weighted Fuzzy Fisherface Algorithm for Face Recognition Using Wavelet TransformEsther Annlin Kala James, S. AnnaduraiProblem statement: The paper addresses the face recognition problem by proposing Weighted Fuzzy Fisherface (WFF) technique using biorthogonal transformation. The weighted fuzzy fisherface technique was an extension of Fisher Face technique by introducing fuzzy class membership to each training sample in calculating the scatter matrices. Approach: In weighted fuzzy fisherface method, weight emphasizes classes that were close together and deemphasizes … …Journal of Computer Science, Vol. 8, Issue 1 · 26 Oct 2011 · 7,345 accessesView PDFCite