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  • Open Access

    ARTICLE

    Sentiment Analysis Using Deep Learning Approach

    Peng Cen1, Kexin Zhang1, Desheng Zheng1, *

    Journal on Artificial Intelligence, Vol.2, No.1, pp. 17-27, 2020, DOI:10.32604/jai.2020.010132 - 15 July 2020

    Abstract Deep learning has made a great breakthrough in the field of speech and image recognition. Mature deep learning neural network has completely changed the field of nat ural language processing (NLP). Due to the enormous amount of data and opinions being produced, shared and transferred everyday across the Internet and other media, sentiment analysis has become one of the most active research fields in natural language processing. This paper introduces three deep learning networks applied in IMDB movie reviews sent iment analysis. Dataset was divided to 50% positive reviews and 50% negative reviews. Recurrent Neural More >

  • Open Access

    ARTICLE

    Classification Algorithm Optimization Based on Triple-GAN

    Kun Fang1, 2, Jianquan Ouyang1, *

    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 >

  • Open Access

    ARTICLE

    Book Retrieval Method Based on QR Code and CBIR Technology

    Qiuyan Wang1, *, Haibing Dong2

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 101-110, 2019, DOI:10.32604/jai.2019.08170

    Abstract It is the development trend of library information management, which applies the mature and cutting-edge information technology to library information retrieval. In order to realize the rapid retrieval of massive book information, this paper proposes a book retrieval method combining QR code with image retrieval technology. This method analyzes the visual features of book images, design a book image retrieval method based on boundary contour and regional pixel distribution features, and realizes the association retrieval of book information combined with the QR code, so as to improve the efficiency of book retrieval. The experimental results More >

  • Open Access

    ARTICLE

    Materials Selection Method Combined with Different MADM Methods

    Won-Chol Yang1.*, Son-Hak Chon1, Chol-Min Choe1, Un-Ha Kim1

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 89-99, 2019, DOI:10.32604/jai.2019.07885

    Abstract Materials selection is a multiple attribute decision making (MADM) problem. A lot of MADM methods are applicable to materials selection, and it may produce considerable differences between the results of materials selection. But it is unknown which MADM method is better. So it is desirable to decide reasonable final result of materials selection in consideration of the individual results from different MADM methods. In this paper, materials selection method combined with different MADM methods is proposed. The method is based on final ranks of alternative materials, where the final ranks are determined from the ranks More >

  • Open Access

    ARTICLE

    Assessing the Forecasting of Comprehensive Loss Incurred by Typhoons: A Combined PCA and BP Neural Network Model

    Shuai Yuan1, Guizhi Wang1,*, Jibo Chen1, Wei Guo2

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 69-88, 2019, DOI:10.32604/jai.2019.06535

    Abstract This paper develops a joint model utilizing the principal component analysis (PCA) and the back propagation (BP) neural network model optimized by the Levenberg Marquardt (LM) algorithm, and as an application of the joint model to investigate the damages caused by typhoons for a coastal province, Fujian Province, China in 2005-2015 (latest). First, the PCA is applied to analyze comprehensively the relationship between hazard factors, hazard bearing factors and disaster factors. Then five integrated indices, overall disaster level, typhoon intensity, damaged condition of houses, medical rescue and self-rescue capability, are extracted through the PCA; Finally,… More >

  • Open Access

    ARTICLE

    A Face Recognition Algorithm Based on LBP-EHMM

    Tao Li1, Lingyun Wang1, Yin Chen1,*, Yongjun Ren1, Lei Wang1, Jinyue Xia2

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 59-68, 2019, DOI:10.32604/jai.2019.06346

    Abstract In order to solve the problem that real-time face recognition is susceptible to illumination changes, this paper proposes a face recognition method that combines Local Binary Patterns (LBP) and Embedded Hidden Markov Model (EHMM). Face recognition method. The method firstly performs LBP preprocessing on the input face image, then extracts the feature vector, and finally sends the extracted feature observation vector to the EHMM for training or recognition. Experiments on multiple face databases show that the proposed algorithm is robust to illumination and improves recognition rate. More >

  • Open Access

    ARTICLE

    A Hybrid Approach of TLBO and EBPNN for Crop Yield Prediction Using Spatial Feature Vectors

    Preeti Tiwari1, *, Piyush Shukla1

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 45-58, 2019, DOI:10.32604/jai.2019.04444

    Abstract The prediction of crop yield is one of the important factor and also challenging, to predict the future crop yield based on various criteria’s. Many advanced technologies are incorporated in the agricultural processes, which enhances the crop yield production efficiency. The process of predicting the crop yield can be done by taking agriculture data, which helps to analyze and make important decisions before and during cultivation. This paper focuses on the prediction of crop yield, where two models of machine learning are developed for this work. One is Modified Convolutional Neural Network (MCNN), and the… More >

  • Open Access

    ARTICLE

    Research on Robot Control Technology Based on Vision Localization

    Ruijiao Yin1, Jie Yang1,*

    Journal on Artificial Intelligence, Vol.1, No.1, pp. 37-44, 2019, DOI:10.32604/jai.2019.05815

    Abstract Based on the understanding of machine vision localization technology at home and abroad, this paper outlines the overall design of the system, and analyses the working principle and workflow of the robot with vision system in workpiece grinding. The hardware design of the system is introduced. The process of image processing is analyzed in detail, and the results of image processing are given. The basic parameters of camera imaging are taken as internal parameters. The camera calibration is obtained by rotation matrix R and translation parameter T. The coordinate transformation of camera coordinate system and More >

  • Open Access

    ARTICLE

    Ship Trajectory Prediction Based on BP Neural Network

    Hai Zhou1,2,*, Yaojie Chen1,2, Sumin Zhang3

    Journal on Artificial Intelligence, Vol.1, No.1, pp. 29-36, 2019, DOI:10.32604/jai.2019.05939

    Abstract In recent years, with the prosperity of world trade, the water transport industry has developed rapidly, the number of ships has surged, and ship safety accidents in busy waters and complex waterways have become more frequent. Predicting the movement of the ship and analyzing the trajectory of the ship are of great significance for improving the safety level of the ship. Aiming at the multi-dimensional characteristics of ship navigation behavior and the accuracy and real-time requirements of ship traffic service system for ship trajectory prediction, a ship navigation trajectory prediction method combining ship automatic identification… More >

  • Open Access

    ARTICLE

    Remaining Useful Life Prediction of Rolling Bearings Based on Recurrent Neural Network

    Yimeng Zhai1, Aidong Deng1,*, Jing Li1,2, Qiang Cheng1, Wei Ren3

    Journal on Artificial Intelligence, Vol.1, No.1, pp. 19-27, 2019, DOI:10.32604/jai.2019.05817

    Abstract In order to acquire the degradation state of rolling bearings and achieve predictive maintenance, this paper proposed a novel Remaining Useful Life (RUL) prediction of rolling bearings based on Long Short Term Memory (LSTM) neural net-work. The method is divided into two parts: feature extraction and RUL prediction. Firstly, a large number of features are extracted from the original vibration signal. After correlation analysis, the features that can better reflect the degradation trend of rolling bearings are selected as input of prediction model. In the part of RUL prediction, LSTM that making full use of More >

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