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

152 articles for “random process”
Set a search alert
Also matching:1 special issue
Research ArticleOpen accessIn the keywordsDistributed and Parallel Decision Forest for Human Activities Prediction: Experimental Analysis on HAR-Smartphones DatasetBudi Padmaja, Venkata Rama Prasad Vaddella, Kota Venkata Naga SunithaSensor-based human motion detection requires the subtle amount of knowledge about various human activities from fitted sensor observations and readings. The prevalent pattern recognition methodologies have made immense progress over recent years. Nonetheless, these kind of methods usually rely on the particular heuristic variable extraction, which could inhibit generalization realization. This paper presents a distributed and parallel decision forest approach … …Journal of Computer Science, Vol. 15, Issue 5 · 11 May 2019 · 7,395 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest-Based Genome Analysis for Disease Association and SNP Marker IdentificationXiangdong LiuAt present, genomic data analysis has the problems of insufficient model interpretation and limited computational efficiency in disease association research. As a powerful machine learning algorithm, Random Forest has demonstrated excellent ability in processing complex and multi-dimensional data sets and has gradually become a popular tool in the field of bioinformatics. The purpose of this paper is to explore how … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 2 · 25 Jul 2025 · 5,536 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,947 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis on User Reviews of Snapchat in IndonesiaEvaristus Didik Madyatmadja, Brigita Christabel Surya Winata, Evelyn Pradhan et al.This research explores the sentiment expressed in Snapchat user reviews within the Indonesian context, leveraging advanced natural language processing techniques and classification models. With a focus on the Indonesian user base, 8,015 reviews from the Google Play Store were analyzed using naive bayes, Support Vector Machines (SVM), and random forest models. The results indicated that the random forest model outperformed … …Journal of Computer Science, Vol. 21, Issue 1 · 2 Jan 2025 · 5,600 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 829 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 · 1,667 accessesView PDFCite
Research ArticleOpen accessIn the abstractBig Data Framework for Predicting Infectious Diseases to Improve Healthcare by Discovering New Symptom PatternsAmal Mohamed Mounir, Mohamed Ibrahim Marie, Laila Abd-ElhamidThe utilization of big data in infectious disease control represents a captivating opportunity, as these novel data streams offer the potential to enhance the timeliness of preventive measures. Various healthcare providers in both the public and private sectors generate, store, and analyse extensive datasets to enhance the quality of services they deliver. Recently, the outbreak of the new coronavirus, COVID-19, … …Journal of Computer Science, Vol. 20, Issue 10 · 2 Aug 2024 · 4,922 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Background Knowledge and Random Sampling in Genetic Programming: A Case Study in Learning Boolean Parity FunctionsLappoon R. TangThe Boolean even-N-parity function returns T (i.e., true) if an even number of its Boolean arguments for N arguments are T and otherwise returns NIL (i.e., false). Learning Boolean even-N-parity functions has been recognized as a difficult problem for evolutionary computation (such as genetic programming) especially when N is large (e.g., 20+). A number of approaches have been proposed for … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 5,489 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,077 accessesView PDFCite