Junhui Wang¹, Wanzi Yan¹, Zhijun Wan^1,*, Yi Wang^2,*, Jiakun Lv¹, Aiping Zhou³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1135-1157, 2020, DOI:10.32604/cmes.2020.014313 - 15 December 2020

Abstract Precise recovery of Coalbed Methane (CBM) based on transparent reconstruction of geological conditions is a branch of intelligent mining. The process of permeability reconstruction, ranging from data perception to real-time data visualization, is applicable to disaster risk warning and intelligent decision-making on gas drainage. In this study, a machine learning method integrating the Random Forest (RF) and the Genetic Algorithm (GA) was established for permeability prediction in the Xishan Coalfield based on Uniaxial Compressive Strength (UCS), effective stress, temperature and gas pressure. A total of 50 sets of data collected by a self-developed apparatus were… More >

Fan Yang^1,2,3,*, Jianwei Ren^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 801-814, 2020, DOI:10.32604/cmes.2020.08889 - 12 October 2020

Abstract Based on the rapid simulation of Markov Chain on samples in failure region, a novel method of reliability analysis combining Monte Carlo Markov Chain (MCMC) with random forest algorithm was proposed. Firstly, a series of samples distributing around limit state function are generated by MCMC. Then, the samples were taken as training data to establish the random forest model. Afterwards, Monte Carlo simulation was used to evaluate the failure probability. Finally, examples demonstrate the proposed method possesses higher computational efficiency and accuracy. More >

Yuqing Yang^{1, 3}, Peng Fu^{2, *}, Xiaojiang Yang^{1, 4}, Hong Hong⁵, Dequn Zhou¹

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2413-2423, 2020, DOI:10.32604/cmc.2020.011881 - 16 September 2020

Abstract Massive Open Online Course (MOOC) has become a popular way of online learning used across the world by millions of people. Meanwhile, a vast amount of information has been collected from the MOOC learners and institutions. Based on the educational data, a lot of researches have been investigated for the prediction of the MOOC learner’s final grade. However, there are still two problems in this research field. The first problem is how to select the most proper features to improve the prediction accuracy, and the second problem is how to use or modify the data… More >

Rizwan Ali Naqvi¹, Muhammad Adnan Khan^{2, *}, Nauman Malik², Shazia Saqib², Tahir Alyas², Dildar Hussain³

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1221-1236, 2020, DOI:10.32604/cmc.2020.011686 - 20 August 2020

Abstract Roman Urdu has been used for text messaging over the Internet for years especially in Indo-Pak Subcontinent. Persons from the subcontinent may speak the same Urdu language but they might be using different scripts for writing. The communication using the Roman characters, which are used in the script of Urdu language on social media, is now considered the most typical standard of communication in an Indian landmass that makes it an expensive information supply. English Text classification is a solved problem but there have been only a few efforts to examine the rich information supply… More >

Kun Fang^{1, 2}, Jianquan Ouyang^{1, *}

Journal on Artificial Intelligence, Vol.2, No.1, pp. 1-15, 2020, DOI:10.32604/jai.2020.09738 - 15 July 2020

Abstract Generating an Adversarial network (GAN) has shown great development prospects in image generation and semi-supervised learning and has evolved into TripleGAN. However, there are still two problems that need to be solved in Triple-GAN: based on the KL divergence distribution structure, gradients are easy to disappear and training instability occurs. Since Triple-GAN tags the samples manually, the manual marking workload is too large. Marked uneven and so on. This article builds on this improved Triple-GAN model (Improved Triple-GAN), which uses Random Forests to classify real samples, automate tagging of leaf nodes, and use Least Squares More >

Junbiao Liu^{1, 6}, Duanpo Wu^{2, 3}, Zimeng Wang², Xinyu Jin^{1, *}, Fang Dong⁴, Lurong Jiang⁵, Chenyi Cai⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 401-426, 2020, DOI:10.32604/cmes.2020.08731 - 01 April 2020

Abstract In the field of medical informatics, sleep staging is a challenging and timeconsuming task undertaken by sleep experts. According to the new standard of the American Academy of Sleep Medicine (AASM), the stages of sleep are divided into wakefulness (W), rapid eye movement (REM) and non-rapid eye movement (NREM) which includes three sleep stages (N1, N2 and N3) that describe the depth of sleep. This study aims to establish an automatic sleep staging algorithm based on the improved weighted random forest (WRF) and Hidden Markov Model (HMM) using only the features extracted from double-channel EEG… More >

Kemal Akyol^1,*, Baha Şen²

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 69-80, 2019, DOI:10.32604/cmc.2019.08143

Abstract The popularity of news, which conveys newsworthy events which occur during day to people, is substantially important for the spectator or audience. People interact with news website and share news links or their opinions. This study uses supervised learning based machine learning techniques in order to predict news popularity in social media sources. These techniques consist of basically two phrases: a) the training data is sent as input to the classifier algorithm, b) the performance of pre-learned algorithm is tested on the testing data. And so, a knowledge discovery from the data is performed. In… More >

Alia Alabdulkarim¹, Mznah Al-Rodhaan², Yuan Tian^*,3, Abdullah Al-Dhelaan²

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 585-601, 2019, DOI:10.32604/cmc.2019.05637

Abstract Clinical decision-support systems are technology-based tools that help healthcare providers enhance the quality of their services to satisfy their patients and earn their trust. These systems are used to improve physicians’ diagnostic processes in terms of speed and accuracy. Using data-mining techniques, a clinical decision support system builds a classification model from hospital’s dataset for diagnosing new patients using their symptoms. In this work, we propose a privacy-preserving clinical decision-support system that uses a privacy-preserving random forest algorithm to diagnose new symptoms without disclosing patients’ information and exposing them to cyber and network attacks. Solving More >

Tang Y¹, SS Jin²

Phyton-International Journal of Experimental Botany, Vol.87, pp. 280-285, 2018, DOI:10.32604/phyton.2018.87.280

Abstract Persistent seed banks have been detected in the Horqin Sandy Land, China using experimental methods. In this study, we used seed traits (i.e. seed mass and seed shape) to predict the persistence of seed banks using the random forest algorithm. The results showed that the mean decrease in accuracy for seed mass and seed shape was 18.26 and 9.90, respectively, suggesting that seed mass was a better predictor than seed shape. With increasing seed mass, the log of P (where P is the ratio of the number of votes selecting existence of a persistent seed… More >

M. Rajalakshmi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.2, pp. 209-220, 2018, DOI:10.3970/cmes.2018.114.209

Abstract Amongst several biometric traits, Vein pattern biometric has drawn much attention among researchers and diverse users. It gains its importance due to its difficulty in reproduction and inherent security advantages. Many research papers have dealt with the topic of new generation biometric solutions such as iris and vein biometrics. However, most implementations have been based on small datasets due to the difficulties in obtaining samples. In this paper, a deeper study has been conducted on previously suggested methods based on Convolutional Neural Networks (CNN) using a larger dataset. Also, modifications are suggested for implementation using More >