International Journal of Fuzzy Computation and Modelling
These articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.
Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.
Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.
International Journal of Fuzzy Computation and Modelling (5 papers in press)
Development of Fuzzy Based Autoregressive Integrated Moving Average Exogenous Input(FARIMAX)Model for Filtration Process by Dauda Araromi, Olajide Ajala, Aminah Sulayman Abstract: Development of black-box model for filtration process has been carried out in this work. Data needed for the model development was obtained through experimental study on filtration unit using aqueous calcium carbonate (CaCO3) slurry. The input and output data generated from the experiment consisted of one manipulated variable (feed pressure, Pr), one disturbance variable (concentration of the solute in the feed, CA0) and one controlled variable (suspension concentration, CA). The data were used to develop a fuzzy model based on autoregressive integrated moving average exogenous input (FARIMAX) structure. Model order selection was carried out based on trial and error while optimal model order was determined using factorial technique. The performance of the developed model was determined using root mean square error (RMSE), coefficient of determination (R2) and model fit. The model gave optimal order [3 3 3 3 1], RMSE (1.855 Keywords: Fuzzy model;FARIMAX model; Black-box model; MATLAB; Modelling; ARIMAX; Filtration process.
Prediction of flood hazard map based on hybrid fuzzy geographic information system and its application for Ayamama Watershed by Hussein BIZIMANA, Abdusselam Altunkaynak Abstract: This research aims to bring a new methodology to early flood management and warning. It proposes modeling one of Istanbul watersheds, the Ayamama watershed in Istanbul, Turkey for possible flood hazard using a new fuzzy-Geographical Information System hybrid approach. It expands the domain of flood hazard early warning and management that usually uses conventional hydraulic and hydrology approaches to a newly developing area of artificial intelligence in flood early warning and management. The research opted for a more technical study using both GIS and MATLAB softwares to model the flood hazard levels in Ayamama watershed. The methodology takes into account three factors to model the flood hazard map. Elevation, Euclidian distance from Ayamama creek and local urbanization degree are the chosen factors. Results on how to identify flood hazard were demonstrated by providing a map of flood hazard zones with their respective negative levels of impacts. Keywords: Fuzzy-GIS; Flood; hazard; prediction; Geographic Information System; Modelling.
Takagi-Sugeno Fuzzy PID Controllers: Mathematical Models and Stability Analysis with Multiple Fuzzy Sets by Ritu Raj, Murali M. Bosukonda Abstract: This paper deals with nonlinear Takagi-Sugeno (TS) fuzzy PID controllers with multiple fuzzy sets. Two models of fuzzy PID controllers are proposed using Algebraic Product (AP) triangular norm, Bounded Sum (BS)/Maximum (Max) triangular co-norm and Center of Gravity (CoG) defuzzifier. The inputs are fuzzified by three or more fuzzy sets with trapezoidal/triangular type membership functions. A new rule base is proposed consisting of four rules which reduce the number of tunable parameters. The models of the fuzzy PID controllers reveal that they are (nonlinear) variable gain/structure controllers, i.e. the gains are a function of input variables and the structure of the controller changes in the input space. The variations of gain and the properties of the controllers are investigated. The Bounded-Input Bounded-Output (BIBO) stability of the closed loop system with one of the proposed models in the loop is studied. The applicability of the controllers is demonstrated with the help of two examples. Keywords: Fuzzy control; Takagi-Sugeno controller; Variable gain controller; Mathematical model; BIBO stability.
A NEW APPROACH TO FIND OPTIMAL SOLUTION OF FUZZY ASSIGNMENT PROBLEM USING PENALTY METHOD FOR HENDECAGONAL FUZZY NUMBER by Revathi Muthukutty, Valliathal M Abstract: Fuzzy Assignment problem (FAP) is a well-known topic and it is used to solve many real-life problems. In many situations, the parameters are used to characterize the uncertainty either triangular or trapezoidal fuzzy number. But the representation of fuzzy number is not always a triangular or trapezoidal fuzzy number. In this paper, a new generalization of fuzzy number called Hendecagonal fuzzy number (HDFN) is introduced with its arithmetic operations. This research aims to introduce a new penalty approach in order to solve fuzzy assignment problem such that the solution is optimum. The cost of assignment is represented by Trapezoidal fuzzy number (TrapFN) and HDFN. The proposed method overcomes the limitations of existing method and HDFN is more optimal than TrapFN. Keywords: Hendecagonal fuzzy number; Alpha cut; Fuzzy arithmetic; Fuzzy Assignment problem.
New Similarity Measures for Pythagorean Fuzzy Sets with Applications by Paul Augustine Ejegwa Abstract: The concept of Pythagorean fuzzy sets (PFSs) is pertinent in finding reliable solution to decision-making problems, because of its unique nature of indeterminacy. Pythagorean fuzzy set is characterized by membership degree, non-membership degree, and indeterminate degree in such a way that the sum of the square of each of the parameters is one. The objective of this paper is to present some new similarity measures for PFSs by incorporating the conventional parameters that describe PFSs, with applications to some real-life decision-making problems. Furthermore, an illustrative example is used to establish the applicability and validity of the proposed similarity measures and compare the results with the existing comparable similarity measures to show the effectiveness of the proposed similarity measures. While analyzing the reliability of the proposed similarity measures in comparison to analogous similarity measures for PFSs in literature, we discover that the proposed similarity measures, especially, $s_4$ yields the most reasonable measure. Finally, we apply $s_4$ to decision-making problems such as career placement, medical diagnosis, and electioneering process. Additional applications of these new similarity measures could be exploited in decision-making of real-life problems embedded with uncertainty such as in multi-criteria decision-making (MCDM) and multi-attribute decision-making (MADM), respectively. Keywords: Fuzzy set; Intuitionistic fuzzy set; Similarity measure; Pythagorean fuzzy set.