Research ArticleOpen accessIn the abstractGlobal Supply Chain: Enhance Production Cost Efficiency Through Machine LearningLoubna Moumeni, Mohammed SaberMachine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provided by machine learning by exploring new areas within the supply chain network. This article delves into Supply Chain Management (SCM) and its broader implications beyond logistics. SCM involves the resources, methods, and … …Journal of Computer Science, Vol. 20, Issue 9 · 14 Jun 2024 · 5,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Exploration of Restaurant Recommender SystemTora Fahrudin, Nelsi WisnaThe exploitation of Recommender Systems (RS) isstill a challenge, hence it is important to explore the three correlatedattributes, such as restaurant, food, and service ratings. Therefore, thisstudy provides an in-depth review of these attribute ratings using theCollaborative Filtering (CF) technique. Experiments were performed with k-NN,SVD, Slope One, and Co-Clustering algorithms, while RMSE, MSE, MAE, and FCPwere used as evaluation metrics. … …Journal of Computer Science, Vol. 18, Issue 8 · 2 Sep 2022 · 6,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Metaheuristic Algorithm for Diseases Classification Using UAV ImagesYagnasree Sirivella, Anuj JainRecent advances in technology are very astounding since they have made it possible to manage and monitor systems remotely. Traditional farming is undergoing a transition towards "smart farming" with the assistance of technological breakthroughs, which include the implementation of intelligent irrigation systems and the remote monitoring of the development of crops. In particular, the Unmanned Aerial Vehicle plays a significant … …Journal of Computer Science, Vol. 19, Issue 10 · 11 Sep 2023 · 5,251 accessesView PDFCite
Research ArticleOpen accessIn the abstractGeometrical Approach to a New Hybrid Grid-Based Gravitational Clustering AlgorithmFaisal Bin Al Abid, A.N.M. Rezaul Karim, Golam Rahman ChowdhuryIn the past years, several clustering algorithms have been developed, for example, K-means, K-medoid. Most of these algorithms have the common problem of selecting the appropriate number of clusters and these algorithms are sensitive to noisy data and would cause less accurate clustering of the data set. Therefore, this paper introduces a new Hybrid Grid-based Gravitational Clustering Algorithm (HGGCA) geometrically, … …Journal of Computer Science, Vol. 17, Issue 3 · 9 Mar 2021 · 6,783 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Plant Leaf Diseases Using K‒mean++ Intermeans Thresholding AlgorithmKittipol Wisaeng, Worawat Sa–NgiamviboolIn the field of agricultural information, the plant leaf disease detection is highly important for both farmer life and environment. To improve the accuracy of plant leaf disease detection and reduce the image processing time, the improved K‒mean++ clustering and intermeans thresholding method are proposed in this study. The proposed algorithms are used for training and testing diseases in plant … …Journal of Computer Science, Vol. 16, Issue 9 · 21 Sep 2020 · 6,750 accessesView PDFCite
Research ArticleOpen accessIn the abstractModified ACS Centroid Memory for Data ClusteringAyad Mohammed Jabbar, Ku Ruhana Ku-Mahamud, Rafid SagbanAnt Colony Optimization (ACO) is a generic algorithm, which has been widely used in different application domains due to its simplicity and adaptiveness to different optimization problems. The key component that governs the search process in this algorithm is the management of its memory model. In contrast to other algorithms, ACO explicitly utilizes an adaptive memory, which is important to … …Journal of Computer Science, Vol. 15, Issue 10 · 11 Oct 2019 · 7,641 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Selection-based MCL Clustering Algorithm for Motif DiscoveryChunxiao Sun, Zhiyong Zhang, Jinglei Tang, Shuai LiuAs motif discovery plays an important role in the understanding of the relationship of gene regulation, this paper puts forward a selection-based MCL clustering refinement algorithm (SMCLR) aiming at solving the planted (l, d) motif search (PMS) problem. Firstly, we divide the DNA dataset into different subsets through selection of reference sequence and screen parts of eligible subsets by setting … …American Journal of Biochemistry and Biotechnology, Vol. 14, Issue 4 · 1 Jan 2019 · 8,827 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Elite Pool-Based Big Bang-Big Crunch Metaheuristic for Data ClusteringIbrahim Al-Marashdeh, Ghaith M. Jaradat, Masri Ayob et al.This paper delves into the capacity of enhanced Big Bang-Big Crunch (EBB-BC) metaheuristic to handle data clustering problems. BB-BC is a product of an evolution theory of the universe in physics and astronomy. Two main phases of BB-BC are big bang and big crunch. The big bang phase involves a creation of a population of random initial solutions, while in … …Journal of Computer Science, Vol. 14, Issue 12 · 19 Jun 2018 · 7,879 accessesView PDFCite
Research NotesOpen accessIn the abstractReal Time Density-Based Clustering (RTDBC) Algorithm for Big DataDr. B. Ravi PrasadDensity Based Spatial Clustering of Applications with Noise (DBSCAN), a well-known Density-Based Clustering Algorithm is a advanced data clustering method with various applications in numerous fields like Satellites images, X-ray crystallography, Anomaly Detection in Temperature Data. But its run time R(n2) complexity draws a major challenge. In this research paper, we propose a new unique algorithm called Real Time Density … …Journal of Computer Science, Vol. 13, Issue 10 · 15 Aug 2017 · 7,298 accessesView PDFCite