Journal of Artificial Intelligence

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Journal on Artificial Intelligence

ISSN: 2579-0021 (print)
ISSN: 2579-003X (online) Publication Frequency: Quarterly

About the Journal

Artificial Intelligence (AI) techniques have been attracted increasing attention around the world and are now being widely used to solve a whole range of hitherto intractable problems. This journal welcomes foundational and applied papers describing mature work involving AI methods.

Current Issue - Vol.2, No.4, 2020 Most Viewed

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ARTICLE
A Survey of Knowledge Based Question Answering with Deep Learning
Chaoyu Deng, Guangfu Zeng, Zhiping Cai, Xiaoqiang Xiao^*
Journal on Artificial Intelligence, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jai.2020.011541
Abstract The purpose of automated question answering is to let the machine understand natural language questions and give accurate answers in the form of natural language. This technology requires the machine to store a large amount of background knowledge. In recent years, the rapid development of knowledge graph has made the knowledge based question answering (KBQA) more and more popular. Traditional styles of KBQA methods mainly include semantic parsing, information extraction and vector modeling. With the development of deep learning, KBQA with deep learning has gradually become the mainstream method. This paper introduces the application of deep learning in KBQA mainly… More
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ARTICLE
Vehicle License Plate Recognition System Based on Deep Learning in Natural Scene
Ze Chen, Leiming Yan^*, Siran Yin, Yuanmin Shi
Journal on Artificial Intelligence, Vol.2, No.4, pp. 167-175, 2020, DOI:10.32604/jai.2020.012716
Abstract With the popularity of intelligent transportation system, license plate recognition system has been widely used in the management of vehicles in and out of closed communities. But in the natural environment such as video monitoring, the performance and accuracy of recognition are not ideal. In this paper, the improved Alex net convolution neural network is used to remove the false license plate in a large range of suspected license plate areas, and then the projection transformation and Hough transformation are used to correct the inclined license plate, so as to build an efficient license plate recognition system in natural environment.… More
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ARTICLE
A Learning Framework for Intelligent Selection of Software Verification Algorithms
Weipeng Cao¹, Zhongwu Xie¹, Xiaofei Zhou², Zhiwu Xu¹, Cong Zhou¹, Georgios Theodoropoulos³, Qiang Wang^3,*
Journal on Artificial Intelligence, Vol.2, No.4, pp. 177-187, 2020, DOI:10.32604/jai.2020.014829
Abstract Software verification is a key technique to ensure the correctness of software. Although numerous verification algorithms and tools have been developed in the past decades, it is still a great challenge for engineers to accurately and quickly choose the appropriate verification techniques for the software at hand. In this work, we propose a general learning framework for the intelligent selection of software verification algorithms, and instantiate the framework with two state-of-the-art learning algorithms: Broad learning (BL) and deep learning (DL). The experimental evaluation shows that the training efficiency of the BL-based model is much higher than the DL-based models and… More
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ARTICLE
Clustering Algorithms: Taxonomy, Comparison, and Empirical Analysis in 2D Datasets
Samih M. Mostafa^1,2,*
Journal on Artificial Intelligence, Vol.2, No.4, pp. 189-215, 2020, DOI:10.32604/jai.2020.014944
Abstract Because of the abundance of clustering methods, comparing between methods and determining which method is proper for a given dataset is crucial. Especially, the availability of huge experimental datasets and transactional and the emerging requirements for data mining and the like needs badly for clustering algorithms that can be applied in various domains. This paper presents essential notions of clustering and offers an overview of the significant features of the most common representative clustering algorithms of clustering categories presented in a comparative way. More specifically the study is based on the numerical type of the data that the algorithm supports,… More
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ARTICLE
A Hybrid Approach of TLBO and EBPNN for Crop Yield Prediction Using Spatial Feature Vectors
Preeti Tiwari^{1, *}, 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 other model is TLBO (Teacher… More
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ARTICLE
Materials Selection Method Combined with Different MADM Methods
Won-Chol Yang^1.*, 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 of the alternative materials using… More
Views:2176 Downloads:1115 Download PDF

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ARTICLE
Book Retrieval Method Based on QR Code and CBIR Technology
Qiuyan Wang^{1, *}, 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 show that, the books can… More
Views:2130 Downloads:852 Download PDF

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ARTICLE
A Face Recognition Algorithm Based on LBP-EHMM
Tao Li¹, Lingyun Wang¹, Yin Chen^1,*, 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
Views:1682 Downloads:844 Download PDF

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Assessing the Forecasting of Comprehensive Loss Incurred by Typhoons: A Combined PCA and BP Neural Network Model
Shuai Yuan¹, Guizhi Wang^1,*, 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, the BP neural network model,… More
Views:1667 Downloads:750 Download PDF

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ARTICLE
Intelligent Mobile Drone System Based on Real-Time Object Detection
Chuanlong Li^1,2, Xingming Sun^1,2,*, Junhao Cai^3,*
Journal on Artificial Intelligence, Vol.1, No.1, pp. 1-8, 2019, DOI:10.32604/jai.2019.06064
Abstract Drone also known as unmanned aerial vehicle (UAV) has drawn lots of attention in recent years. Quadcopter as one of the most popular drones has great potential in both industrial and academic fields. Quadcopter drones are capable of taking off vertically and flying towards any direction. Traditional researches of drones mainly focus on their mechanical structures and movement control. The aircraft movement is usually controlled by a remote controller manually or the trajectory is pre-programmed with specific algorithms. Consumer drones typically use mobile device together with remote controllers to realize flight control and video transmission. Implementing different functions on mobile… More
Views:1489 Downloads:942 Download PDF