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Author

Han Ding

Bio: Han Ding is an academic researcher from Hubei University. The author has contributed to research in topics: Graph (abstract data type) & Wait-for graph. The author has an hindex of 1, co-authored 4 publications receiving 1 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors proposed an evaluation method for e-commerce site based on neural network, which can greatly extend auto evaluation and reduce the arbitrary of the manual evaluation, thereby increasing the objectivity and accuracy of the evaluation.
Abstract: With the development of the Internet, e-commerce is developing rapidly. E-commerce website plays an increasingly important role in e-commerce. The site operators need to know the popularity of the site and the site's success and inadequacies, and to find ways to further improve. Website investors need to know the operational status of the site, brand strength and potential for development. Consumers need to understand e-commerce services and product quality, business reputation. These need to be a comprehensive evaluation of the site. This article first analyzes the current state of domestic and international e-commerce site evaluation studies, and then proposes the evaluation method for e-commerce site based on neural network. Relative to the traditional manual and subjective evaluation, this method can greatly extend auto evaluation and reduce the arbitrary of the manual evaluation, thereby increasing the objectivity and accuracy of the evaluation.

1 citations

Journal ArticleDOI
Yi Wang1, Han Ding1, Fan Yang1
TL;DR: A test method for process deadlock based on graph grammars through constructing process resource diagram that can construct and judge the validity of the process resource diagrams and test if there is the deadlock in the process.
Abstract: This paper proposes a test method for process deadlock based on graph grammars through constructing process resource diagram. Through using the construction rules, it can construct and judge the validity of the process resource diagram. Through using the test rules, it can test if there is the deadlock in the process. The method is a graphical approach; it is simple and intuitive with strong operability. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4945
Journal ArticleDOI
TL;DR: A method for computer aided organic synthesis based on two-dimensional graph grammars that could apply the basic principle of the graph Grammars to effectively and efficiently solve organic synthesis problems is presented.
Abstract: Traditionally, computer aided organic synthesis is based on the one-dimensional string model that employs string grammars to tackle the structure of molecular; the processing of organic reactions, and the establishment of the knowledge bases and file systems. Because of the limitations of one-dimensional method for tackling two-dimensional issues like organic syntheses, this paper presents a method for computer aided organic synthesis based on two-dimensional graph grammars. The method could apply the basic principle of the graph grammars to effectively and efficiently solve organic synthesis problems.
Journal ArticleDOI
Yi Wang1, Han Ding1, Fan Yang1
TL;DR: This paper proposed a evaluation method based on neural networks, based on the indexed of the analytic hierarchy process, through using the expert evaluation samples, by the BP neural network to study, so as to get the objective weight of the indexes, and then reflect the real situation of the evaluation objects.
Abstract: In human social life, it is often need to make comprehensive evaluation for person, thing , or a project to carry on the classification or evaluation. Analytic hierarchy process is relatively common and the most simple evaluation model. It draw up a series of evaluation index according to the evaluation object. The index may contain multiple child index, according to the relationship between the indexes or artificial factors to determine tie index weight, and get the overall evaluation for objects. The artificial factor is too much, it can not objectively reflect the real situation of the evaluation object. This paper proposed a evaluation method based on neural networks, based on the indexed of the analytic hierarchy process, through using the expert evaluation samples, by the BP neural network to study, so as to get the objective weight of the indexes, and then reflect the real situation of the evaluation objects.
Journal ArticleDOI
TL;DR: A new multi-head attention mechanism focusing on data positional information is designed, and a novel MHA-based fault diagnosis method is developed and extended to the fault diagnosis scenario with missing information.
Abstract: In order to make full use of the absolute position information of fault signal, this paper designs a new multi-head attention (MHA) mechanism focusing on data positional information, proposes a novel MHA-based fault diagnosis method and extends it to the fault diagnosis scenario with missing information. Based on the absolute positional information and the trainable parameter matrix of the fault data, a novel attention weight matrix is generated, and the fault features are extracted by a fully connected network with the attention mechanism. By integrating the positional information into the weight matrix, the new MHA mechanism has the ability to extract more effective data features, compared with the traditional MHA method. Furthermore, the proposed method is also developed for the fault diagnosis scenarios with missing information. A special attention weight modified method is designed to reduce the impact of missing data on fault diagnosis results. In the experiment simulations, the data sampled from ZHS-2 multi-function motor flexible rotor test bed and the Tennessee- Eastman process data are utilized to test the performance of the algorithm. The results show that the proposed method can effectively extract fault features and reduce the impact of missing data.

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Proceedings ArticleDOI
01 Dec 2016
TL;DR: Twitter data is utilized for big data analytics and several Twitter performance indexes are proposed to assist the website performance evaluation of E-commerce websites in Saudi Arabia.
Abstract: E-commerce plays a key role in business success nowadays. Therefore, the performance of E-commerce websites is critical. E-commerce websites generate a large amount of data that is often used for performance evaluation. Many website evaluation methods have been proposed, but the social media factor is usually not taken into consideration. In this paper, Twitter data is utilized for big data analytics and several Twitter performance indexes are proposed to assist the website performance evaluation. The result is compared with the performance evaluation result using several commercial tools for 13 selected E-commerce websites in Saudi Arabia.

3 citations