Journal of Intelligent & Fuzzy Systems - Volume 28, issue 4

Authors: Vidhya, P.M. | Paul, Varghese

Article Type: Research Article

Abstract: Recent researches regarding information hiding is mostly concentrating on Linguistic steganography. The Steganography is the art and science of hiding a message inside another message without drawing any suspicion to the others so that the message can only be detected by its intended recipient. Now days, concentration is made on local language encryption based steganography to provide high security for the secret information sharing. In this paper, a method to steganography is proposed with an Indian local language, Malayalam. The proposed method consists of a custom Unicode based technique with embedding based on indexing, i.e. the original message is encoded …to a Malayalam text with custom UNICODE values generated for the Malayalam text. After that an embedding algorithm will be designed to mix the encoded original message with the Malayalam text. The experimental study was done to evaluate the efficiency of the proposed approach. The comparison study of the proposed method against an existing method revealed that, the proposed steganography methods is more precise in the encoding process and balanced in the decoding process. The proposed method achieved a precision rate of .95 and decoding rate of .81. Show more

Keywords: Information hiding, text steganography, UNICODE, index

DOI: 10.3233/IFS-141444

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1591-1600, 2015

Authors: Yetilmezsoy, Kaan | Ozgun, Hale | Dereli, Recep Kaan | Ersahin, Mustafa Evren | Ozturk, Izzet

Article Type: Research Article

Abstract: In this study, an adaptive neuro-fuzzy inference system (ANFIS) including five process variables, such as influent chemical oxygen demand, influent flow rate, influent total Kjeldahl nitrogen, effluent volatile fatty acids and effluent bicarbonate, was described to predict the effluent chemical oxygen demand load from a full-scale expanded granular sludge bed reactor (EGSBR) treating corn processing wastewater. The proposed ANFIS model was conducted by applying hybrid learning algorithm and the model performance was tested by the means of distinct test data set randomly selected from the experimental domain. The ANFIS-based predictions were also validated using various descriptive statistical indicators, such as …root mean-square error, index of agreement, the factor of two, fractional variance, proportion of systematic error, etc. The lowest root mean square error (RMSE = 0.03655) and the highest determination coefficient (R2 = 0.958) were achieved with the subtractive clustering of a first-order Sugeno type fuzzy inference system. ANFIS predicted results were compared with the outputs of multiple nonlinear regression analysis-based models derived in the scope of the present work. Statistical performance indices computed for the testing data set proved that the developed ANFIS-based model exhibited a very good precision in predicting the effluent chemical oxygen demand, load for the EGSBR system. Due to high capability of the ANFIS model in capturing the dynamic behavior and non-linear interactions, it was demonstrated that a complex system, such as anaerobic digestion, could be easily modeled. Show more

Keywords: Adaptive neuro-fuzzy inference system, anaerobic digestion, corn processing wastewaters, expanded granular sludge bed reactor, modeling

DOI: 10.3233/IFS-141445

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1601-1616, 2015

Authors: Mokhtarnejad, Fatemeh | Ezzati, Reza

Article Type: Research Article

Abstract: In this paper, we propose a successive approximation method based on fuzzy wavelet like operator for the approximate solution of nonlinear Hammerstein fuzzy integral equations (NHFIE). For this purpose, the convergence conditions and an error estimate are given. Finally, to show the efficiency of presented method, some test problems, for which the exact solution is known, are considered.

Keywords: Nonlinear fuzzy integral equation, Hammerstein fuzzy integral equation, fuzzy wavelet like operator, successive approximation method

DOI: 10.3233/IFS-141446

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1617-1626, 2015

Authors: Qin, Zhongfeng | Wen, Meilin

Article Type: Research Article

Abstract: A complex stochastic process is a fundamental connection between two-dimensional stochastic processes. Similarly, a complex fuzzy process will connect two fuzzy processes to describe the spacial dynamic fuzzy phenomena. In this paper, we first give the formal definitions of complex fuzzy process and complex Liu process. And then the complex differential and complex Liu integral of complex Liu process are also studied in this paper. Especially, some properties of analytic functions of complex Liu process are proved. Finally, complex fuzzy differential equations are proposed as the extension of general fuzzy differential equation. The obtained results provide fundamentals and promote the …development of fuzzy calculus. Show more

Keywords: Fuzzy process, credibility measure, fuzzy variable, complex Liu process, Liu process

DOI: 10.3233/IFS-141448

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1627-1633, 2015

Authors: Wang, Jinfeng | Leung, Kwongsak | Lee, Kinhong | Wang, Wenzhong

Article Type: Research Article

Abstract: In this study, a new classification model - Multiple Nonlinear Integral with Multiple projections is proposed, which includes Double Nonlinear Integral extending to new variants for adapting for complicated data distribution and enhancing classification accuracy. When the performance is not satisfying by projecting with classical Nonlinear Integral, the second projection is need to stretch data in one dimension space to two dimension space. The value of two projection forms the 2-dimensional coordinates. All data in two-dimensional space can be classified by a straight line easily. The rest may be deduced by analogy, if the result is still not good for …decision, the Multiple Nonlinear Integral can repeat n times double projections, in which n will be an optimized value to balance the performance and the complexity. The repeating can help adjust the data distribution in 2-dimensional space until being classified easily. The classification model based on Multiple Nonlinear Integral is applied to two kinds of datasets. One kind comes from the classical database; another kind is the real data about the HBV (Hepatitis B Virus) collected from hospital. The experimental results show that the new model has better performance compared with the classical algorithm and the classical Nonlinear Integral. Especially to the HBV data, Multiple Nonlinear Integral presents the superior on diagnosis to the others. Show more

Keywords: Nonlinear integral, multiple projections, generalization, classification

DOI: 10.3233/IFS-141449

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1635-1645, 2015

Authors: Khalid, Asma | Awais, Mian Muhammad

Article Type: Research Article

Abstract: Consensus is understood as a unanimous agreement by all experts in a group. The goal of consensus is not the selection of several options but to develop one decision that suits the interests of the entire group under consideration. In this paper, it is assumed that collective preferences are developed with the help of commonly used ordered weighted averaging operators but resultant relations do not exhibit any property of a consensus type. That is, consensus is not reached at the first attempt of ranking alternatives. Under such circumstances, the measure of distance to consensus can be successfully used to determine …how far a group collectively is from consensus. The aim of this paper is to compare, where possible, the distance to consensus of collective relations compiled with the help of most commonly used ordered weighted averaging operators. The innovative part is that this measure helps in defining an upper and lower bound of distance to consensus of the resultant collective relations. With such an analysis at hand, experts can choose a suitable ordered weighting averaging operator to formulate a collective relation that exhibits a lower distance to consensus. Show more

Keywords: Distance to consensus, ordered weighted averaging operators, reciprocal relations, collective preference relations

DOI: 10.3233/IFS-141450

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1647-1657, 2015

Authors: Anjali, N. | Mathew, Sunil

Article Type: Research Article

Abstract: In this paper, we introduce block of a fuzzy graph. It generalizes the concept of blocks of a graph. Depending on the nature of blocks, we identify a particular class of fuzzy graphs named K2 block graphs and characterize them using strongest strong cycles. We also define fuzzy star and obtain a lower bound for number of blocks in fuzzy stars. A possible application of block of a fuzzy graph is also included.

Keywords: Block of a fuzzy graph, strongest strong cycle, $K_2$ block graph

DOI: 10.3233/IFS-141451

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1659-1665, 2015

Authors: Chen, Hung-Yi

Article Type: Research Article

Abstract: The laser surface alloying quality may vary significantly with respect to the process parameters variation. Hence, a feedback control system is required to monitor the operating parameters for yielding a good quality control. Since this multi-input and multi-output system has nonlinear coupling and time varying dynamic characteristics, it is very difficult to establish an accurate process model for designing model-based controller. Hence a hybrid model-free adaptive fuzzy and neural network controller (HAFNC), which combines an adaptive rule with fuzzy and neural network control, is employed in this study to overcome the difficulty. It has on-line learning ability for responding to …the system's nonlinear and time-varying behaviors. Since this model-free controller has simple control structure and small number of control parameters, it is easy to implement. Two HAFNC controllers are designed for tuning the laser power and the traverse velocity simultaneously to tackle the absorptivity and geometrical variations of the work pieces. Simulation results based on semi-experimental system dynamic model and parameters show that the good surface lapping performance is achieved by using this intelligent control strategy. Show more

Keywords: Laser alloying, hybrid adaptive fuzzy and neural network control, on-line learning

DOI: 10.3233/IFS-141453

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1667-1676, 2015

Authors: Farshi, Mehdi | Davvaz, Bijan | Mirvakili, Saeed

Article Type: Research Article

Abstract: In this paper, the notion of weak transposition Fn -hypergroups as a subclass of fuzzy transposition n-ary hypergroups (transposition Fn -hypergroups) is introduced and several properties are found and examples are presented. We show that transposition Fn -hypergroups are a generalization of F-polygroups, Fn -polygroups and join Fn -spaces. Finally, we prove that the class of Fn -polygroups and faint regular weak transposition Fn -hypergroups coincide.

Keywords: n-hypergroup, $F^n$-polygroup, $F^n$-hypergroup, faint regular, regular, weak transposition

DOI: 10.3233/IFS-141454

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1677-1685, 2015

Authors: Zhan, Jianming | Liu, Qi | Davvaz, Bijan

Article Type: Research Article

Abstract: The aim of this paper is to introduce the notion of a rough soft hemiring, which is an extended notion of a rough hemiring and a soft hemiring. We study roughness in soft hemirings with respect to Pawlak approximation spaces. Some new rough soft operations are explored. In particular, lower and upper rough soft hemirings and (k-idealistic, h-idealistic, strong h-idealistic) idealistic soft hemirings are investigated. Finally, an important result on an upper strong h-idealistic rough soft hemiring via Bourne's congruence relations are obtained.

Keywords: Rough hemiring, soft hemiring, congruence relation, rough soft hemiring

DOI: 10.3233/IFS-141455

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1687-1697, 2015