Yizhi Liu^{1, 2}, Xuesong Wang^{1, 2}, Jianxun Liu^{1, 2, *}, Zhuhua Liao^{1, 2}, Yijiang Zhao^{1, 2}, Jianjun Wang^{1, 2}

Journal on Artificial Intelligence, Vol.2, No.3, pp. 137-148, 2020, DOI:10.32604/jai.2020.010620

Abstract Cruising route recommendation based on trajectory mining can improve taxidrivers' income and reduce energy consumption. However, existing methods mostly recommend pick-up points for taxis only. Moreover, their performance is not good enough since there lacks a good evaluation model for the pick-up points. Therefore, we propose an entropy-based model for recommendation of taxis' cruising route. Firstly, we select more positional attributes from historical pick-up points in order to obtain accurate spatial-temporal features. Secondly, the information entropy of spatial-temporal features is integrated in the evaluation model. Then it is applied for getting the next pick-up points and further recommending a series… More >

Yabin Xu^{1, 2, 3, *}, Ting Xu³, Xiaowei Xu⁴

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1075-1089, 2020, DOI:10.32604/cmc.2020.09849

Abstract To improve the attack detection capability of content centric network (CCN), we propose a detection method of interest flooding attack (IFA) making use of the feature of self-similarity of traffic and the information entropy of content name of interest packet. On the one hand, taking advantage of the characteristics of self-similarity is very sensitive to traffic changes, calculating the Hurst index of the traffic, to identify initial IFA attacks. On the other hand, according to the randomness of user requests, calculating the information entropy of content name of the interest packets, to detect the severity of the IFA attack, is.… More >

Lihua Yin1, Ran Li^{1, 2, *}, Jingquan Ding^{3, 4, 5, *}, Xiao Li^{3, 4, 5}, Yunchuan Guo², Huibing Zhang⁶, Ang Li⁷

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1323-1342, 2020, DOI:10.32604/cmc.2020.09667

Abstract With the rapid development of mobile wireless Internet and high-precision localization devices, location-based services (LBS) bring more convenience for people over recent years. In LBS, if the original location data are directly provided, serious privacy problems raise. As a response to these problems, a large number of location-privacy protection mechanisms (LPPMs) (including formal LPPMs, FLPPMs, etc.) and their evaluation metrics have been proposed to prevent personal location information from being leakage and quantify privacy leakage. However, existing schemes independently consider FLPPMs and evaluation metrics, without synergizing them into a unifying framework. In this paper, a unified model is proposed to… More >

Alireza Poordavoodi¹, Mohammad Reza Moazami Goudarzi^2,*, Hamid Haj Seyyed Javadi³, Amir Masoud Rahmani⁴, Mohammad Izadikhah⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.2, pp. 525-570, 2020, DOI:10.32604/cmes.2020.08854

Abstract With the growing number of Web services on the internet, there is a challenge to select the best Web service which can offer more quality-of-service (QoS) values at the lowest price. Another challenge is the uncertainty of QoS values over time due to the unpredictable nature of the internet. In this paper, we modify the interval data envelopment analysis (DEA) models [Wang, Greatbanks and Yang (2005)] for QoS-aware Web service selection considering the uncertainty of QoS attributes in the presence of desirable and undesirable factors. We conduct a set of experiments using a synthesized dataset to show the capabilities of… More >

Mohamed A. El-Sayed^{1, *}, Abdelmgeid A. Ali², Mohamed E. Hussien³, Hameda A. Sennary³

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 1-16, 2020, DOI:10.32604/cmc.2020.08444

Abstract The essential tool in image processing, computer vision and machine vision is edge detection, especially in the fields of feature extraction and feature detection. Entropy is a basic area in information theory. The entropy, in image processing field has a role associated with image settings. As an initial step in image processing, the entropy is always used the image’s segmentation to determine the regions of image which is used to separate the background and objects in image. Image segmentation known as the process which divides the image into multiple regions or sets of pixels. Many applications have been development to… More >

Yanghong Zhang¹, Feng Sun², Liwei Tian¹, Jinfeng Li³, Longqing Zhang³, Shengfu Lan³

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 817-831, 2020, DOI:10.32604/cmc.2020.06076

Abstract Image sparse representation is a method of efficient compression and coding of image signal in the process of digital image processing. Image after sparse representation, to enhance the transmission efficiency of the image signal. Entropy of Primitive (EoP) is a statistical representation of the sparse representation of the image, which indicates the probability of each base element. Based on the EoP, this paper presents an image quality evaluation method-Difference of Visual Information Metric (DVIM). The principle of this method is to evaluate the image quality with the difference between the original image and the distorted image. The comparative experiments between… More >

Mohamed Abd El-Aziz^{1, 2}, A. M. Aly^{1, 3, *}

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 37-59, 2020, DOI:10.32604/cmc.2020.08488

Abstract In the present study, the effects of the magnetic field on the entropy generation during fluid flow and heat transfer of a Sisko-fluid over an exponentially stretching surface are considered. The similarity transformations are used to transfer the governing partial differential equations into a set of nonlinear-coupled ordinary differential equations. Runge-Kutta-Fehlberg method is used to solve the governing problem. The effects of magnetic field parameter M, local slip parameter λ, generalized Biot number γ, Sisko fluid material parameter A, Eckert number Ec, Prandtl number Pr and Brinkman number Br at two values of power law index on the velocity, temperature,… More >

Shuangsheng Zhang^1,5, Hanhu Liu¹, Jing Qiang^2,*, Hongze Gao^3,*, Diego Galar⁴, Jing Lin⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 373-394, 2019, DOI:10.32604/cmes.2019.03825

Abstract Coupling Bayes’ Theorem with a two-dimensional (2D) groundwater solute advection-diffusion transport equation allows an inverse model to be established to identify a set of contamination source parameters including source intensity (M ), release location ( X₀ , Y₀) and release time (T₀), based on monitoring well data. To address the issues of insufficient monitoring wells or weak correlation between monitoring data and model parameters, a monitoring well design optimization approach was developed based on the Bayesian formula and information entropy. To demonstrate how the model works, an exemplar problem with an instantaneous release of a contaminant in a confined groundwater… More >

Yuehan Du^1,2, Ruoyu Zhang¹, Xu Zhang¹, Antai Ouyang³, Xiaodong Zhang⁴, Jinyong Cheng¹, Wenpeng Lu^1,*

Journal of Quantum Computing, Vol.1, No.1, pp. 21-28, 2019, DOI:10.32604/jqc.2019.06063

Abstract The algorithm based on combination learning usually is superior to a single classification algorithm on the task of protein secondary structure prediction. However, the assignment of the weight of the base classifier usually lacks decision-making evidence. In this paper, we propose a protein secondary structure prediction method with dynamic self-adaptation combination strategy based on entropy, where the weights are assigned according to the entropy of posterior probabilities outputted by base classifiers. The higher entropy value means a lower weight for the base classifier. The final structure prediction is decided by the weighted combination of posterior probabilities. Extensive experiments on CB513… More >

S. Hernández^1,2, A. Baldomir¹, J. Díaz¹, F. Pereira¹

CMC-Computers, Materials & Continua, Vol.32, No.3, pp. 219-240, 2012, DOI:10.3970/cmc.2012.032.219

Abstract A numerical optimization method was proposed time ago by Templeman based on the maximum entropy principle. That approach combined the Kuhn-Tucker condition and the information theory postulates to create a probabilistic formulation of the optimality criteria techniques. Such approach has been enhanced in this research organizing the mathematical process in a single optimization loop and linearizing the constraints. It turns out that such procedure transforms the optimization process in a sequence of systems of linear equations which is a very efficient way of obtaining the optimum solution of the problem. Some examples of structural optimization, namely, a planar truss, a… More >