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  • Open Access

    ARTICLE

    Highway Cost Prediction Based on LSSVM Optimized by Intial Parameters

    Xueqing Wang1, Shuang Liu1,*, Lejun Zhang2

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 259-269, 2021, DOI:10.32604/csse.2021.014343 - 23 December 2020

    Abstract The cost of highway is affected by many factors. Its composition and calculation are complicated and have great ambiguity. Calculating the cost of highway according to the traditional highway engineering estimation method is a completely tedious task. Constructing a highway cost prediction model can forecast the value promptly and improve the accuracy of highway engineering cost. This work sorts out and collects 60 sets of measured data of highway engineering; establishes an expressway cost index system based on 10 factors, including main route mileage, roadbed width, roadbed earthwork, and number of bridges; and processes the More >

  • Open Access

    ARTICLE

    Fused and Modified Evolutionary Optimization of Multiple Intelligent Systems Using ANN, SVM Approaches

    Jalal Sadoon Hameed Al-bayati1,*, Burak Berk Üstündağ2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1479-1496, 2021, DOI:10.32604/cmc.2020.013329 - 26 November 2020

    Abstract The Fused Modified Grasshopper Optimization Algorithm has been proposed, which selects the most specific feature sets from images of the disease of plant leaves. The Proposed algorithm ensures the detection of diseases during the early stages of the diagnosis of leaf disease by farmers and, finally, the crop needed to be controlled by farmers to ensure the survival and protection of plants. In this study, a novel approach has been suggested based on the standard optimization algorithm for grasshopper and the selection of features. Leaf conditions in plants are a major factor in reducing crop… More >

  • Open Access

    ARTICLE

    Performance Estimation of Machine Learning Algorithms in the Factor Analysis of COVID-19 Dataset

    Ashutosh Kumar Dubey1,*, Sushil Narang1, Abhishek Kumar1, Satya Murthy Sasubilli2, Vicente García-Díaz3

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1921-1936, 2021, DOI:10.32604/cmc.2020.012151 - 26 November 2020

    Abstract Novel Coronavirus Disease (COVID-19) is a communicable disease that originated during December 2019, when China officially informed the World Health Organization (WHO) regarding the constellation of cases of the disease in the city of Wuhan. Subsequently, the disease started spreading to the rest of the world. Until this point in time, no specific vaccine or medicine is available for the prevention and cure of the disease. Several research works are being carried out in the fields of medicinal and pharmaceutical sciences aided by data analytics and machine learning in the direction of treatment and early… More >

  • Open Access

    ARTICLE

    A Novel Hybrid Intelligent Prediction Model for Valley Deformation: A Case Study in Xiluodu Reservoir Region, China

    Mengcheng Sun1,2, Weiya Xu1,2,*, Huanling Wang1,3, Qingxiang Meng1,2, Long Yan1,2, Wei-Chau Xie4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 1057-1074, 2021, DOI:10.32604/cmc.2020.012537 - 30 October 2020

    Abstract The narrowing deformation of reservoir valley during the initial operation period threatens the long-term safety of the dam, and an accurate prediction of valley deformation (VD) remains a challenging part of risk mitigation. In order to enhance the accuracy of VD prediction, a novel hybrid model combining Ensemble empirical mode decomposition based interval threshold denoising (EEMD-ITD), Differential evolutions—Shuffled frog leaping algorithm (DE-SFLA) and Least squares support vector machine (LSSVM) is proposed. The non-stationary VD series is firstly decomposed into several stationary subseries by EEMD; then, ITD is applied for redundant information denoising on special sub-series,… More >

  • Open Access

    ARTICLE

    Text Classification for Azerbaijani Language Using Machine Learning

    Umid Suleymanov1, Behnam Kiani Kalejahi1,2,*, Elkhan Amrahov1, Rashid Badirkhanli1

    Computer Systems Science and Engineering, Vol.35, No.6, pp. 467-475, 2020, DOI:10.32604/csse.2020.35.467

    Abstract Text classification systems will help to solve the text clustering problem in the Azerbaijani language. There are some text-classification applications for foreign languages, but we tried to build a newly developed system to solve this problem for the Azerbaijani language. Firstly, we tried to find out potential practice areas. The system will be useful in a lot of areas. It will be mostly used in news feed categorization. News websites can automatically categorize news into classes such as sports, business, education, science, etc. The system is also used in sentiment analysis for product reviews. For More >

  • Open Access

    ARTICLE

    Emotion Recognition Using WT-SVM in Human-Computer Interaction

    Zequn Wang, Rui Jiao, Huiping Jiang*

    Journal of New Media, Vol.2, No.3, pp. 121-130, 2020, DOI:10.32604/jnm.2020.010674 - 04 September 2020

    Abstract With the continuous development of the computer, people's requirements for computers are also getting more and more, so the brain-computer interface system (BCI) has become an essential part of computer research. Emotion recognition is an important task for the computer to understand social status in BCI. Affective computing (AC) aims to develop the model of emotions and advance the affective intelligence of computers. There are various emotion recognition approaches. The method based on electroencephalogram (EEG) is more reliable because it is higher in accuracy and more objective in evaluation than other external appearance clues such… More >

  • Open Access

    ARTICLE

    Color Image Segmentation Using Soft Rough Fuzzy-C-Means and Local Binary Pattern

    R.V.V. Krishna1,*, S. Srinivas Kumar2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 281-290, 2020, DOI:10.31209/2019.100000121

    Abstract In this paper, a color image segmentation algorithm is proposed by extracting both texture and color features and applying them to the one -against-all multi class support vector machine (MSVM) classifier for segmentation. Local Binary Pattern is used for extracting the textural features and L*a*b color model is used for obtaining the color features. The MSVM is trained using the samples obtained from a novel soft rough fuzzy c-means (SRFCM) clustering. The fuzzy set based membership functions capably handle the problem of overlapping clusters. The lower and upper approximation concepts of rough sets deal well More >

  • Open Access

    ARTICLE

    Chinese Spirits Identification Model Based on Mid-Infrared Spectrum

    Wu Zeng1, Zhanxiong Huo1, *, Yuxuan Xie2, Yingxiang Jiang1, Kun Hu1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1869-1883, 2020, DOI:10.32604/cmc.2020.010139 - 30 June 2020

    Abstract Applying computer technology to the field of food safety, and how to identify liquor quickly and accurately, is of vital importance and has become a research focus. In this paper, sparse principal component analysis (SPCA) was applied to seek sparse factors of the mid-infrared (MIR) spectra of five famous vintage year Chinese spirits. The results showed while meeting the maximum explained variance, 23 sparse principal components (PCs) were selected as features in a support vector machine (SVM) model, which obtained a 97% classification accuracy. By comparison principal component analysis (PCA) selected 10 PCs as features More >

  • Open Access

    ARTICLE

    Using Audiometric Data to Weigh and Prioritize Factors that Affect Workers’ Hearing Loss through Support Vector Machine (SVM) Algorithm

    Hossein ElahiShirvan1, MohammadReza Ghotbi-Ravandi2, Sajad Zare3,*, Mostafa Ghazizadeh Ahsaee4

    Sound & Vibration, Vol.54, No.2, pp. 99-112, 2020, DOI:10.32604/sv.2020.08839 - 09 May 2020

    Abstract Workers’ exposure to excessive noise is a big universal work-related challenges. One of the major consequences of exposure to noise is permanent or transient hearing loss. The current study sought to utilize audiometric data to weigh and prioritize the factors affecting workers’ hearing loss based using the Support Vector Machine (SVM) algorithm. This cross sectional-descriptive study was conducted in 2017 in a mining industry in southeast Iran. The participating workers (n = 150) were divided into three groups of 50 based on the sound pressure level to which they were exposed (two experimental groups and… More >

  • Open Access

    ARTICLE

    State-Based Control Feature Extraction for Effective Anomaly Detection in Process Industries

    Ming Wan1, Jinfang Li1, Jiangyuan Yao2, *, Rongbing Wang1, 3, Hao Luo1

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1415-1431, 2020, DOI:10.32604/cmc.2020.09692 - 30 April 2020

    Abstract In process industries, the characteristics of industrial activities focus on the integrality and continuity of production process, which can contribute to excavating the appropriate features for industrial anomaly detection. From this perspective, this paper proposes a novel state-based control feature extraction approach, which regards the finite control operations as different states. Furthermore, the procedure of state transition can adequately express the change of successive control operations, and the statistical information between different states can be used to calculate the feature values. Additionally, OCSVM (One Class Support Vector Machine) and BPNN (BP Neural Network), which are More >

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