Journal of Artificial Intelligence

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.3, No.2, 2021 Most Viewed

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ARTICLE
A Generation Method of Letter-Level Adversarial Samples
Huixuan Xu¹, Chunlai Du¹, Yanhui Guo^2,*, Zhijian Cui¹, Haibo Bai¹
Journal on Artificial Intelligence, Vol.3, No.2, pp. 45-53, 2021, DOI:10.32604/jai.2021.016305
Abstract In recent years, with the rapid development of natural language processing, the security issues related to it have attracted more and more attention. Character perturbation is a common security problem. It can try to completely modify the input classification judgment of the target program without people’s attention by adding, deleting, or replacing several characters, which can reduce the effectiveness of the classifier. Although the current research has provided various methods of perturbation attacks on characters, the success rate of some methods is still not ideal. This paper mainly studies the sample generation of optimal perturbation characters and proposes a characterlevel… More
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ARTICLE
Evaluation Model of Farmer Training Effect Based on AHP–A Case Study of Hainan Province
Shengjie Li, Chaosheng Tang^*
Journal on Artificial Intelligence, Vol.3, No.2, pp. 55-62, 2021, DOI:10.32604/jai.2021.017408
Abstract On the basis of studying the influencing factors of training effect evaluation, this paper constructs an AHP-fuzzy comprehensive evaluation model for farmers’ vocational training activities in Hainan Province to evaluate farmers’ training effect, which overcomes the limitations of traditional methods. Firstly, the content and index system of farmer training effect evaluation are established by analytic hierarchy process, and the weight value of each index is determined. Then, the fuzzy comprehensive evaluation (FCE) of farmer training effect is carried out by using multi-level FCE. The joint use of AHP and FCE improves the reliability and effectiveness of the evaluation process and… More
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ARTICLE
Hybrid Efficient Convolution Operators for Visual Tracking
Yu Wang^*
Journal on Artificial Intelligence, Vol.3, No.2, pp. 63-72, 2021, DOI:10.32604/jai.2021.010455
Abstract Visual tracking is a classical computer vision problem with many applications. Efficient convolution operators (ECO) is one of the most outstanding visual tracking algorithms in recent years, it has shown great performance using discriminative correlation filter (DCF) together with HOG, color maps and VGGNet features. Inspired by new deep learning models, this paper propose a hybrid efficient convolution operators integrating fully convolution network (FCN) and residual network (ResNet) for visual tracking, where FCN and ResNet are introduced in our proposed method to segment the objects from backgrounds and extract hierarchical feature maps of objects, respectively. Compared with the traditional VGGNet,… More
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Semantic Link Network Based Knowledge Graph Representation and Construction
Weiyu Guo^1,*, Ruixiang Jia¹, Ying Zhang²
Journal on Artificial Intelligence, Vol.3, No.2, pp. 73-79, 2021, DOI:10.32604/jai.2021.018648
Abstract A knowledge graph consists of a set of interconnected typed entities and their attributes, which shows a better performance to organize, manage and understand knowledge. However, because knowledge graphs contain a lot of knowledge triples, it is difficult to directly display to researchers. Semantic Link Network is an attempt, and it can deal with the construction, representation and reasoning of semantics naturally. Based on the Semantic Link Network, this paper explores the representation and construction of knowledge graph, and develops an academic knowledge graph prototype system to realize the representation, construction and visualization of knowledge graph. More
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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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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
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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
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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
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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
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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:2015 Downloads:1149 Download PDF