Fundamenta Informaticae - Volume 133, issue 1

Authors: Dutta, Soma | Chakraborty, Mihir Kr.

Article Type: Research Article

Abstract: Fuzzy Logic a la Pavelka has been reintroduced here in terms of consequence relation instead of consequence operator. Metalogical notions like, consistency and inconsistency are proposed as graded notions. The relationship between consequence relation and inconsistency, both fuzzy here, is studied. Another metalogical notion viz., equivalence of two sets of formulae that originates from Tarski is defined and investigated in this context when the premise is a fuzzy set.

Keywords: Fuzzy set of premises, Consequence operator, Graded consequence relation

DOI: 10.3233/FI-2014-1059

Citation: Fundamenta Informaticae, vol. 133, no. 1, pp. 1-18, 2014

Authors: Tapaswini, Smita | Chakraverty, S.

Article Type: Research Article

Abstract: This paper investigates the numerical solution of uncertain fractional order diffusion equation subject to various external forces. Homotopy Perturbation Method (HPM) is used for the analysis. Uncertainties present in the system are modelled through triangular convex normalised fuzzy sets. A new computational technique has been proposed based on double parametric form of fuzzy numbers to handle the fuzzy fractional diffusion equation. Using the single parametric form of fuzzy numbers, the original fuzzy fractional diffusion equation is converted first to an interval fuzzy fractional differential equation. Next this equation is transformed to crisp form by applying double parametric form of fuzzy …numbers. Finally the same is solved by HPM symbolically to obtain the uncertain bounds of the solution. Obtained results are depicted in term of plots. Results obtained by the proposed method are compared with existing results in special cases. Show more

Keywords: triangular fuzzy number, double parametric form of fuzzy number, fuzzy fractional diffusion equation, homotopy perturbation method

DOI: 10.3233/FI-2014-1060

Citation: Fundamenta Informaticae, vol. 133, no. 1, pp. 19-34, 2014

Authors: Xia, Yingjie | Zhang, Ting | Wang, Shengbao

Article Type: Research Article

Abstract: This paper presents a method to capture the computational intensity and computing resource requirements of data analysis in intelligent transportation systems (ITS). These requirements can be transformed into a generic methodological framework for Cyber-ITS, mainly consisting of region-based ITS data divisions and tasks scheduling for processing, to support the efficient use of cyber-infrastructure (CI). To characterize the computational intensity of a particular ITS data analysis, the computational transformation is performed by data-centric and operation-centric transformation functions. The application of this framework is illustrated by two ITS data analysis cases: multi-sensor data fusion for traffic state estimation by integrating rough set …theory with Dempster-Shafer (D-S) evidence theory, and geospatial computation on Global Positioning System (GPS) data for advertising value evaluation. To make the design of generic parallel computing solutions feasible for ITS data analysis in these cases, an approach is developed to decouple the region-based division from specific high performance computer (HPC) architecture and implement a prototype of the methodological framework. Experimental results show that the prototype implementation of the framework can be applied to divide the ITS data analysis into a load-balanced set of computing tasks, therefore facilitating the parallelized data fusion and geospatial computation to achieve remarkable speedup in computation time and throughput, without loss in accuracy. Show more

Keywords: Intelligent Transportation Systems, Cyber-infrastructure, Computational Intensity, Framework

DOI: 10.3233/FI-2014-1061

Citation: Fundamenta Informaticae, vol. 133, no. 1, pp. 35-53, 2014

Authors: Xu, Changlin | Wang, Guoyin | Zhang, Qinghua

Article Type: Research Article

Abstract: The representation and processing of uncertainty information is one of the key basic issues of the intelligent information processing in the face of growing vast information, especially in the era of network. There have been many theories, such as probability statistics, evidence theory, fuzzy set, rough set, cloud model, etc., to deal with uncertainty information from different perspectives, and they have been applied into obtaining the rules and knowledge from amount of data, for example, data mining, knowledge discovery, machine learning, expert system, etc. Simply, This is a cognitive transformation process from data to knowledge (FDtoK). However, the cognitive transformation …process from knowledge to data (FKtoD) is what often happens in human brain, but it is lack of research. As an effective cognition model, cloud model provides a cognitive transformation way to realize both processes of FDtoK and FKtoD via forward cloud transformation (FCT) and backward cloud transformation (BCT). In this paper, the authors introduce the FCT and BCT firstly, and make a depth analysis for the two existing single-step BCT algorithms. We find that these two BCT algorithms lack stability and sometimes are invalid. For this reason we propose a new multi-step backward cloud transformation algorithm based on sampling with replacement (MBCT-SR) which is more precise than the existing methods. Furthermore, the effectiveness and convergence of new method is analyzed in detail, and how to set the parameters m, r appeared in MBCT-SR is also analyzed. Finally, we have error analysis and comparison to demonstrate the efficiency of the proposed backward cloud transformation algorithm for some simulation experiments. Show more

Keywords: Concept expression, Cognitive transformation, Normal cloud model, Backward cloud transformation, Mean squared error

DOI: 10.3233/FI-2014-1062

Citation: Fundamenta Informaticae, vol. 133, no. 1, pp. 55-85, 2014

Authors: Ye, Ruisong

Article Type: Research Article

Abstract: In this paper, a generalized multi-sawtooth map based image encryption scheme with an efficient permutation-diffusion mechanism is proposed. In the permutation process, a generalized multi-sawtooth map is utilized to generate one chaotic orbit used to get one index order sequence for the permutation of image pixel positions, while in the diffusion process, two generalized multi-sawtooth maps are employed to yield two pseudo-random grey value sequences for a two-way diffusion of pixel grey values. The yielded grey value sequences are not only sensitive to the control parameters and initial conditions of the considered chaotic maps, but also strongly depend on the …plain-image processed, therefore the proposed scheme can effectively resist statistical attack, differential attack, known-plaintext as well as chosen-plaintext attack. Experimental results show that the new image encryption scheme has satisfactory security thanks to its large key space and robust permutation-diffusion mechanism, which makes it a potential candidate for designing image encryption schemes. Show more

Keywords: generalized multi-sawtooth map, chaotic system, image encryption, permutation, diffusion

DOI: 10.3233/FI-2014-1063

Citation: Fundamenta Informaticae, vol. 133, no. 1, pp. 87-104, 2014