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

Authors: Khan, Sajid Ali | Usman, Muhammad | Riaz, Naveed

Article Type: Research Article

Abstract: Face recognition has received considerable attention in the field of computer vision and pattern recognition. The important applications of face recognition include but are not limited to Airport security, card security in ATM's, visa processing and the passport verification. Although there has been rigorous research in this area for almost a decade, the scientists have not been able to provide and agree to a standard for obtaining the salient information in facial images utilizing feature's categories. In this article, we have presented an approach where features are collected containing local and global face information (i.e. geometric and appearance-based features). These …features are fused, resulting in an increase in the face-recognition accuracy. First, the global features are obtained by utilizing Discrete Cosine Transform and Local facial features via Local Binary Pattern. In the next stage, both local and global features are combined using the concatenation method resulting in an increase in features. To reduce the data dimensions, Particle Swarm Optimization (PSO) along with Genetic Algorithm (GA) is applied to eliminate the redundant features that provide the optimized feature sets. We also provide empirical results of our proposed system. The system has been evaluated using ORL and Labeled Faces in the Wild (LFW) face databases. We have been able to obtain a promising 98% accuracy rate by using PSO-GA based optimized features albeit the reduced number of features. Features' fusion enables proposed system to be robust to variations like facial expression change, illumination effects and occlusions. Show more

Keywords: Face recognition, optimized features, global features, local features, discrete cosine transform, local binary pattern

DOI: 10.3233/IFS-141468

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1819-1828, 2015

Authors: Flaut, Cristina

Article Type: Research Article

Abstract: In this paper, we will provide an algorithm which allows us to find a BCK-algebra starting from a given binary block code.

Keywords: BCK-algebras, block codes

DOI: 10.3233/IFS-141469

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1829-1833, 2015

Authors: Zhao, Qianyi | Chen, Huayou | Zhou, Ligang | Tao, Zhifu | Liu, Xi

Article Type: Research Article

Abstract: This paper investigates the multi-criteria group decision making under fuzzy number intuitionistic fuzzy environment, where the criteria and the decision makers are in different priority level. We propose the non-negative score function for fuzzy number intuitionistic fuzzy number, and we present some fuzzy number intuitionistic fuzzy prioritized operators by extending the prioritized aggregation operators, including the fuzzy number intuitionistic fuzzy prioritized weighted average (FNIFPWA) operator, the fuzzy number intuitionistic fuzzy prioritized weighted geometric (FNIFPWG) operator. We also analyze some of their desirable properties in details. Furthermore, based on these operators, we develop an approach to multi-criteria group decision with fuzzy …number intuitionistic fuzzy information. Finally, we give an illustrative example to show that the developed approach is feasible and effective. Show more

Keywords: Multi-criteria group decision making, fuzzy number intuitionistic fuzzy set, aggregation operator, prioritized weighted average operator

DOI: 10.3233/IFS-141470

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1835-1848, 2015

Authors: Haider, Sajjad | Raza, Syed Ali

Article Type: Research Article

Abstract: The model building of Influence Nets, a special instance of Bayesian belief networks, is a time-consuming and labor-intensive task. No formal process exists that decision makers/system analyst, who are typically not familiar with the underlying theory and assumptions of belief networks, can use to build concise and easy-to-interpret models. In many cases, the developed model is extremely dense, that is, it has a very high link-to-node ratio. The complexity of a network makes the already intractable task of belief updating more difficult. The problem is further intensified in dynamic domains where the structure of the built model is repeated for …multiple time-slices. It is, therefore, desirable to do a post-processing of the developed models and to remove arcs having a negligible influence on the variable(s) of interests. The paper applies sensitivity of arc analysis to identify arcs that can be removed from an Influence Net without having a significant impact on its inferencing capability. A metric is suggested to gauge changes in the joint distribution of variables before and after the arc removal process. The results are benchmarked against the KL divergence metric. An empirical study based on several real Influence Nets is conducted to test the performance of the sensitivity of arc analysis in reducing the model complexity of an Influence Net without causing a significant change in its joint probability distribution. Show more

Keywords: Bayesian networks, influence nets, sensitivity analysis, model building

DOI: 10.3233/IFS-141471

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1849-1859, 2015

Authors: Mezei, József | Björk, Kaj-Mikael

Article Type: Research Article

Abstract: Optimization models combining Economic Production Quantity models and fuzzy set theory are important to the process industry as they are capable of modeling the numerous uncertainties inherent in this context. In this paper, we incorporate backorders (i.e the inventory to go below zero) in a fuzzy Economic Production Quantity (EPQ) model. The uncertainties in the backorders for different products are modeled using triangular possibility distributions. We present an example describing a typical decision making problem in the paper industry to illustrate our model.

Keywords: Inventory management, fuzzy numbers, EOQ-model, production-inventory optimization, supply chain management

DOI: 10.3233/IFS-141472

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1861-1868, 2015

Authors: Azimirad, Ehsan | Haddadnia, Javad

Article Type: Research Article

Abstract: Removing noise from the color images is a very active research scope in image processing. In this paper, a new fuzzy based image filtering algorithm is proposed for reducing and removing impulse noise in color images. For dealing with the Impulse noise, an algorithm is developed to search for a set of uncorrupted pixels in the neighborhood of the pixel of interest and to compute the median of this set. A modified fuzzy filter consisting of two sub filters with novel membership functions is proposed to cancel out the impulse noise. The first sub filter detects the noisy pixel by …utilizing three fuzzy membership functions, defined for this purpose. The corrupted pixels are then corrected using the median of the noise free pixels. The second sub filter makes use of the relation between different color components of a pixel to remove the residual noise in the color image. Simulation results shows that the proposed fuzzy filter effectively removes the additive noise by preserving fine details in the image. Show more

Keywords: Impulse noise, fuzzy filter, reducing noise, median filter, membership functions

DOI: 10.3233/IFS-141473

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1869-1876, 2015

Authors: Li, Deng-Feng | Ren, Hai-Ping

Article Type: Research Article

Abstract: Imprecision and vagueness often occur in practical multi-attribute decision making (MADM) problems. Intuitionistic fuzzy (IF) sets are flexible to simulate these situations. The aim of this paper is to develop an effective method for solving MADM problems in which the attribute values are expressed with IF sets. Inspired by TOPSIS, we propose a new ranking function of IF sets, which takes into the amount and the reliability of an IF set. Hereby we develop a new MADM method. An example of the investment selection problem is examined to demonstrate applicability and feasibility of the proposed method. It is shown that …the proposed method has some advantages over other methods. Show more

Keywords: Intuitionistic fuzzy set, multi-attribute decision making, TOPSIS, ranking function

DOI: 10.3233/IFS-141475

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1877-1883, 2015

Authors: Tang, Yiming | Ren, Fuji

Article Type: Research Article

Abstract: To reveal the inherent essence of current differently implicational algorithms for fuzzy inference, the variable differently implicational algorithm is put forward and investigated. The differently implicational principles are improved from variable and generalized viewpoint. Furthermore, focusing on the FMP (fuzzy modus ponens) problem, unified forms of the new algorithm are obtained for R-implications and S-implications. Following that, the optimal differently implicational solutions are achieved for several specific R-implications and S-implications. Lastly, the new algorithm makes the current differently implicational algorithms compose a united whole.

Keywords: Fuzzy inference, fuzzy modus ponens, fuzzy implication, compositional rule of inference, fully implicational algorithm

DOI: 10.3233/IFS-141476

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1885-1897, 2015

Authors: Mahapatra, G.S. | Mahapatra, B.S. | Roy, P.K.

Article Type: Research Article

Abstract: All most all systems in the field of science and technology are well complicated by the advent of modernity. Complex system reliability is mainly dependant on the credibility of its components. It is very difficult to evaluate precise value of component's reliability at the beginning stage of reliability evaluation, due to unavailable or inadequate information. In this respect, fuzzy reliability variable can play an important role in complex system reliability evaluation. In this paper, a fuzzy reliability variable based fuzzy non-linear programming problem is formulated to maximize the complex system reliability. Symmetrical trapezoidal fuzzy numbers are used as fuzzy variable …for the component's reliability. Since fuzzy variable for optimization is not well defined, we first reduced the problem to an equivalent multi-objective non-linear programming problem. The proposed approach is applied on landing system of Boeing 747D airplane to evaluate the system reliability in fuzzy environment. The proposed approach and the complex system reliability model are well substantiated by providing numerical examples. Show more

Keywords: Fuzzy variable, fuzzy non-linear programming, reliability, symmetric trapezoidal fuzzy number, complex system

DOI: 10.3233/IFS-141477

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1899-1908, 2015

Authors: Salari, Mostafa | Bagherpour, Morteza | Reihani, Mohammad Hossein

Article Type: Research Article

Abstract: Time–cost trade-off problems (TCT) are well-known in project management contents. This approach normally applied for scheduling of a project especially where the project should be completed under pre-determined deadline. This paper aims to extend time-cost trade-off (TCT) problems in order to provide a well-organized mechanism for both scheduling and rescheduling processes of a project. The proposed mechanism includes project scheduling which concerns with the TCT problem, monitoring of project performance during execution phase using earned value management (EVM), and also predicting project future performance through statistical modeling. Once the predicted values of project performance indicate the necessity for rescheduling, the …initial TCT problem is modified to determine a new mode for the execution of the project. In the proposed model, also several options have been considered with specific time and cost for an individual activity where options indicate different execution methods (EM) for the implementation of the whole project. Furthermore, due to vagueness and impreciseness associated with data of real case projects, the time and cost behavior of each option presumed as fuzzy numbers. The proposed control mechanism can help project managers to take the advantage of a comprehensive model to schedule, control, and reschedule a project through the life cycle. An illustrative case is then presented to successfully demonstrate the application of the proposed approach. Show more

Keywords: Time-cost trade-off, fuzzy logic, earned value, fuzzy regression, rescheduling

DOI: 10.3233/IFS-141478

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1909-1919, 2015

Authors: Zhang, Jing | Lei, Hang

Article Type: Research Article

Abstract: Effective acquisition of transition probability matrix is directly related to Internetware reliability computation. The characteristics of Markov chain in Internetware are discussed and analyzed, the construction of Markov chain and the acquisition of transition probability of Internetware are studied, the Internetware model based on Markov chain is constructed. Quantitative calculation method of transition probability based on the smallest quadratic difference is presented by using the occupancy of component executing the transition as the sample statistics to calculate transition probability. The approximation algorithm for computing transition probability matrix based on the modified projection gradient is designed, and it effectively guarantees the …transition law of Markov chain and the characteristics of transition probability matrix. The experiment proves that the presented method and the designed algorithm can effectively compute transition probability matrix with great value in Internetware reliability computation. Show more

Keywords: Internetware, transition probability, matrix, compute method, algorithm

DOI: 10.3233/IFS-141479

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1921-1930, 2015

Authors: Savaş, Ekrem

Article Type: Research Article

Abstract: In this paper, we introduce new notions, namely, ideal statistical convergence and ideal lacunary statistical convergence for fuzzy numbers, their relationship and also make some observations about these classes.

Keywords: Ideal, ideal statistical convergence, ideal lacunary statistical convergence, fuzzy number sequence

DOI: 10.3233/IFS-141480

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1931-1936, 2015

Authors: Gholizade-Narm, Hossein | Shafiee Chafi, Mohammad Reza

Article Type: Research Article

Abstract: In this paper, a new perspective is presented for prediction of chaotic time series by combining the phase space reconstruction and fuzzy approach. Before applying time series to the predictor system, the reconstruction parameters, including embedding dimension and time delay, are determined in an off-line manner by using nearest neighbor and mutual information methods. Then, the structure of the fuzzy system is specified and the input number of fuzzy system is set to the embedding dimensions. According to the embedding dimension and time delay, the phase space is reconstructed point-by-point at the entry of the fuzzy system. Fuzzy system is …composed of two separated parts: predictor and tracker. The predictor part forecasts the next point for new entry with fine-tuned parameters using the last step, and the tracker part adjusts the parameters for the next step. This adjustment is done iteratively. The proposed method is compared with some references' results. Simplicity and appropriate speed with sufficient accuracy are the advantages of this method. Show more

Keywords: Chaos, time series, fuzzy method, forecasting

DOI: 10.3233/IFS-141481

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1937-1946, 2015