A. M. E. Ramírez-Mendoza¹

CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.3, pp. 295-311, 2018, DOI:10.3970/cmes.2018.00239

Abstract A spike response model (SRM) based on the spikes generator circuit (SGC) of adaptive fuzzy spiking neurons (AFSNs) is developed. The SRM is simulated in MatlabTM environment. The proposed model is applied to a configuration of a fuzzy exclusive or (fuzzy XOR) operator, as an illustrative example. A description of the comparison of AFSNs with other similar methods is given. The novel method of the AFSNs is used to determine the value of the weights or parameters of the fuzzy XOR, first with dynamic weights or self-tuning parameters that adapt continuously, then with fixed weights More >

Shengbiao Wu^1,2,3, Weihua Cao^1,3,*, Can Liu^1,3, Min Wu^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.116, No.3, pp. 433-453, 2018, DOI:10.31614/cmes.2018.03309

Abstract A computer-aided tuning method that combines T-S fuzzy neural network (T-S FNN) and offers improved space mapping (SM) is presented in this study. This method consists of three main aspects. First, the coupling matrix is effectively extracted under the influence of phase shift and cavity loss after the initial tuning. Second, the surrogate model is realized by using a T-S FNN based on subspace clustering. Third, the mapping relationship between the actual and the surrogate models is established by the improved space mapping algorithm, and the optimal position of the tuning screws are found by More >

Sunil Kr. Jha¹, Zulfiqar Ahmad²

CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.4, pp. 443-459, 2017, DOI:10.3970/cmes.2017.113.443

Abstract Microbial population and enzyme activities are the significant indicators of soil strength. Soil microbial dynamics characterize microbial population and enzyme activities. The present study explores the development of efficient predictive modeling systems for the estimation of specific soil microbial dynamics, like rock phosphate solubilization, bacterial population, and ACC-deaminase activity. More specifically, optimized subtractive clustering (SC) and Wang and Mendel's (WM) fuzzy inference systems (FIS) have been implemented with the objective to achieve the best estimation accuracy of microbial dynamics. Experimental measurements were performed using controlled pot experiment using minimal salt media with rock phosphate as More >

Susom Dutta¹, A. Ramach,ra Murthy², Dookie Kim³, Pijush Samui⁴

CMC-Computers, Materials & Continua, Vol.53, No.2, pp. 157-174, 2017, DOI:10.3970/cmc.2017.053.167

Abstract In the present scenario, computational modeling has gained much importance for the prediction of the properties of concrete. This paper depicts that how computational intelligence can be applied for the prediction of compressive strength of Self Compacting Concrete (SCC). Three models, namely, Extreme Learning Machine (ELM), Adaptive Neuro Fuzzy Inference System (ANFIS) and Multi Adaptive Regression Spline (MARS) have been employed in the present study for the prediction of compressive strength of self compacting concrete. The contents of cement (c), sand (s), coarse aggregate (a), fly ash (f), water/powder (w/p) ratio and superplasticizer (sp) dosage More >

Jaideep Kaur¹, Kamaljit Kaur²

CMC-Computers, Materials & Continua, Vol.53, No.1, pp. 23-36, 2017, DOI:10.3970/cmc.2017.053.024

Abstract The ubiquitous Internet of Things (IoT) through RFIDs, GPS, NFC and other wireless devices is capable of sensing the activities being carried around Industrial environment so as to automate industrial processes. In almost every industry, employee performance appraisal is done manually which may lead to favoritisms. This paper proposes a framework to perform automatic employee performance appraisal based on data sensed from IoT. The framework classifies raw IoT data into three activities (Positive, Negative, Neutral), co-locates employee and activity in order to calculate employee implication and then performs cognitive decision making using fuzzy logic. From More >

Diptiranjan Behera^1,2, Hong-Zhong Huang¹, S. Chakraverty³

CMES-Computer Modeling in Engineering & Sciences, Vol.108, No.2, pp. 67-87, 2015, DOI:10.3970/cmes.2015.108.067

Abstract Fuzzy systems of linear equations play a vital role in various applications of engineering, science and finance problems. This paper proposes a new method for solving Fully Fuzzy System of Linear Equations (FFSLE) using the linear programming problem approach. There is no restriction on the elements of coefficient matrix. The proposed method is able to solve the system, when the elements of the fuzzy unknown vector are both non-negative and non-positive. Triangular convex normalized fuzzy sets are considered for the present analysis. Known example problems are solved and compared with the results of existing methods More >

Ş. Emrah Amrahov¹, N. A. Gasilov², A. G. Fatullayev²

CMES-Computer Modeling in Engineering & Sciences, Vol.99, No.5, pp. 351-369, 2014, DOI:10.3970/cmes.2014.099.351

Abstract In this paper, we present a new approach to a time-optimal control problem with uncertainties. The dynamics of the controlled object, expressed by a linear system of differential equations, is assumed to be crisp, while the initial and final phase states are fuzzy sets. We interpret the problem as a set of crisp problems. We introduce a new notion of fuzzy optimal time and transform its calculation to two classical time-optimal control problems with initial and final sets. We examine the proposed approach on an example which is a problem of fuzzy control of mathematical More >

R.D. Phillips¹, M.S. Hossain¹, L.T. Watson^1,2, R.H. Wynne³, Naren Ramakrishnan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.97, No.2, pp. 175-197, 2014, DOI:10.3970/cmes.2014.097.175

Abstract Clusters, typically mined by modeling locality of attribute spaces, are often evaluated for their ability to demonstrate ‘enrichment’ of categorical features. A cluster enrichment procedure evaluates the membership of a cluster for significant representation in predefined categories of interest. While classical enrichment procedures assume a hard clustering definition, this paper introduces a new statistical test that computes enrichments for soft clusters. Application of the new test to several scientific datasets is given. More >

S. Chakraverty^1,2, Smita Tapaswini¹

CMES-Computer Modeling in Engineering & Sciences, Vol.103, No.2, pp. 71-90, 2014, DOI:10.3970/cmes.2014.103.071

Abstract Fractional Fornberg-Whitham equation has a vast application in physics. There exist various investigations for the above problem by considering the variables and parameters as crisp/exact. In practice, we may not have these parameters exactly but those may be known in some uncertain form. In the present paper, these uncertainties are taken as interval/fuzzy and the authors proposed here a new method viz. that of the double parametric form of fuzzy numbers to handle the uncertain fractional Fornberg-Whitham equation. Using the single parametric form of fuzzy numbers, original fuzzy fractional Fornberg-Whitham equation is converted first to More >

Diptiranjan Behera¹, Snehashish Chakraverty²

CMES-Computer Modeling in Engineering & Sciences, Vol.96, No.5, pp. 317-337, 2013, DOI:10.3970/cmes.2013.096.317

Abstract This paper targets to analyse the static response of structures with fuzzy parameters using fuzzy finite element method. Here the material, geometrical properties and external load applied to the structures are taken as uncertain. Uncertainties presents in the parameters are modelled through convex normalised fuzzy sets. Fuzzy finite element method converts the problem into fuzzy or fully fuzzy system of linear equations for static analysis. As such here, two new methods are proposed to solve the fuzzy and fully fuzzy system of linear equations. Numerical examples for structures with uncertain system parameters that are in More >