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About IJMLC

International Journal of Machine Learning and Computing (IJMLC) is an international academic open access journal which gains a foothold in Singapore, Asia and opens to the world. It aims to promote the integration of machine learning and computing. The focus is to publish papers on state-of-the-art machine learning and computing. Submitted papers will be reviewed by technical committees of the Journal and Association. The audience includes researchers, managers and operators for machine learning and computing as well as designers and developers.

All submitted articles should report original, previously unpublished research results, experimental or theoretical, and will be peer-reviewed. Articles submitted to the journal should meet these criteria and must not be under consideration for publication elsewhere. Manuscripts should follow the style of the journal and are subject to both review and editing.

Important Notice: IJMLC will only accept new submissions through online submission system. 


General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: ijmlc@ejournal.net

Editor-in-Chief

Prof. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

Latest Articles

01MellisAI - An AI Generated Music Composer Using RNN-LSTMs
N. Hari Kumar, P. S Ashwin, and Haritha Ananthakrishnan

Abstract—The art of composing music can be automated with deep learning along with the knowledge of a few implicit heuristics. In this proposed paper, we aim at building a model that composes Carnatic oriented contemporary tune,[Click]

02Efficient Machine Learning Methods for Hard Disk Drive Yield Prediction Improvement
Anusara Hirunyawanakul, Nittaya Kerdprasop, and Kittisak Kerdprasop

Abstract—Deployment of machine learning techniques are prevailing in world-wide problem solving. Hard disk drive manufacturing is another prominent field seeking for the application of these knowledge intensive techniques.[Click]

03Monte-Carlo Based Reinforcement Learning (MCRL)
Muath Alrammal and Munir Naveed

Abstract—This paper presents a Monte-Carlo based Reinforcement Learning approach called MCRL. MCRL is applied in different domains to construct context-aware model for mobile computing. For mobile devices, we present MCRL, [Click]

04The CAN FD Vehicle Network System with Machine Learning and Scheduling Algorithms
Yung-Hoh Sheu, Cheng-Yo Huang, Chen-Yu Yang, and Yi-Hong Lin

Abstract—The controller area network with flexible datarate (CAN FD) inherits the primary features of a controller area network (CAN); thus, exploring the possibility of establishing a hybrid CAN and CAN FD network is essential. [Click]

05Stock Performance Classification in Stock Exchange of Thailand (SET) by Using Supervised Machine Learning Model
Chayanant Kosol and Punnamee Sachakamol

Abstract—Most investors decide to invest in a stock market in order to win from an inflation. And, Financial Statement is the top tool that Thai investors have been using a financial statement to support their buying/selling decision in the stock market[Click]

More Latest Articles

Most cited papers

01Vehicle Detection and Type Classification Based on CNN-SVM
Stephen Karungaru, Lyu Dongyang, and Kenji Terada

Abstract—In this paper, we propose vehicle detection and classification in a real road environment using a modifi [Click]

02Smartphone Sensor Accelerometer Data for Human Activity Recognition Using Spiking Neural Network
Nor Surayahani Suriani and Fadilla ‘Atyka Nor Rashid

Abstract—Recognizing human actions is a challenging task and actively research in computer vision community The t [Click]

03POETS: A Parallel Cluster Architecture for Spiking Neural Network
Mahyar Shahsavari, Jonathan Beaumont, David Thomas, and Andrew D. Brown

Abstract—Spiking Neural Networks (SNNs) are known as a branch of neuromorphic computing and are currently used in [Click]

04Tuning Parameters in Deep Belief Networks for Time Series Prediction through Harmony Search
Do Ngoc Luu, Nguyen Ngoc Phien, and Duong Tuan Anh

Abstract—There have been several researches of applying Deep Belief Networks (DBNs) to predict time series data [Click]

05Exploring the Adaptation of Recurrent Neural Network Approaches for Extracting Drug–Drug Interactions from Biomedical Text
Wen-Juan Hou and Bamfa Ceesay

Abstract—Information extraction (IE) is the process of automatically identifying structured information from unstruct [Click]

06Enhance System Utilization and Business Revenue with AI-based Queue Reservation System
V. Limlawan and P. Anussornnitisarn

Abstract—Queue management is a crucial part of service industry Business has to deal with the uncertainty of ar [Click]

More Articles

Conferences

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What's New

  • 25

    Mar

    Vol.10, No.2 has been published with online version. [Click]

  • 03

    Aug

    The papers published in Vol.11, No.4 have all received dois from Crossref.[Click]

  • 09

    Jul

    Vol.12, No.3 has been published with online version.[Click]
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