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

Authors: Golshannavaz, Sajjad | Afsharnia, Saeed

Article Type: Research Article

Abstract: This paper proposes an optimal day-ahead (DA) operational scheduling framework to be implemented in distribution management systems (DMSs) as the core of decision makings in active distribution networks (ADNs). Belonging to the new emerging and prosperous technology namely smart distribution grids, the contextualized ADN is composed of active elements including both renewable-based and conventional distributed generations (DGs) as well as demand side management programs. Also, the information and communication technology (ICT) infrastructures are well-equipped in the network which enriches the distribution system operator (DSO) to have a remote and online control on active elements whenever needed. The proposed day-ahead optimal …operational framework firstly schedules the next 24-hour dispatches of DGs, responsive loads (RLs) as well as electricity purchase from wholesale market aiming to minimize the total operation costs. In the first strategy, DGs are supposed to be operated within the mandatory range of reactive support without any financial compensation. Subsequently as an innovative point, the costs of reactive power purchases from both wholesale market and active elements of ADN are judicially included in the scheduling process wherein DGs are contemplated to be utilized in adaptive power factor mode up to a pre-specified minimum value considering financial reimbursements. In contradiction to the conventional fixed pricing mechanisms, a more practical approach for reactive support of DGs is considered and the effect of higher participation of active elements in reactive power provision are thoroughly interrogated in enhancing the economical and technical issues. Also, having a proper control on DGs operating power factor has resulted in extra released capacity which could be exploited to cover the network uncertainties such as wind speed or load variation during a day. The established model is formulated as a mixed integer non-linear problem and solved using binary genetic algorithm. A 33-bus ADN is considered to verify the performance of the proposed optimal operation framework. Show more

Keywords: Smart active distribution networks, distribution management system, distributed generation, adaptive power factor mode, responsive loads, optimal operation scheduling

DOI: 10.3233/IFS-141456

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1699-1711, 2015

Authors: Babitha, K.V. | John, Sunil Jacob

Article Type: Research Article

Abstract: Soft set is a completely generic mathematical tool for modeling uncertainties. Topology is a branch of mathematics, whose concepts exist not only in almost all branches of mathematics, but also in many real life applications. This paper mainly focuses on soft continuous functions and soft product topology. The concept soft homeomorphism and soft subbasis is also introduced and results based on these concepts are also obtained. It is also introduced the concept of soft connectedness and soft compactness. Moreover separation axioms on soft topological space are also studied and derived some relationship among these concepts.

Keywords: Soft topology, soft continuous function, soft homeomorphism, soft product topology, soft compactness, soft separation axioms

DOI: 10.3233/IFS-141457

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1713-1722, 2015

Authors: Baraldi, Piero | Di Maio, Francesco | Rigamonti, Marco | Zio, Enrico | Seraoui, Redouane

Article Type: Research Article

Abstract: We consider a real industrial case concerning 148 shut-down multidimensional transients of a nuclear power plant (NPP) turbine. The objective is to identify groups of transients with similar functional behaviors, and distinguish transients with peculiar behaviors which can be representative of anomalous conditions in the turbine. This objective is pursued by analyzing 7 vibration signals referred to the turbine shaft. The novelty of the work consists in transforming the signals into the “turbine speed-domain” for aligning them according to the turbine speed, so as to easily recognize outlier transients and then performing a fuzzy similarity analysis based on pointwise differences. …Spectral analysis and Fuzzy C-Means (FMC) clustering are applied to identify the turbine anomalous conditions. Show more

Keywords: Fault diagnosis, spectral clustering, Fuzzy C-Means, vibration signals

DOI: 10.3233/IFS-141459

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1723-1731, 2015

Authors: Kula, Ufuk | Ocaktan, Beyazıt

Article Type: Research Article

Abstract: Real life stochastic problems are generally large-scale, difficult to model, and therefore, suffer from the curses of dimensionality. Such problems cannot be solved by classical optimization methods. This paper presents a reinforcement learning algorithm using a fuzzy inference system, ANFIS to find an approximate solution for semi Markov decision problems (SMDPs). The performance of the developed algorithm is measured and compared to a classical reinforcement algorithm, SMART in a numerical example. Our numerical examples show that the developed algorithm converges significantly faster as the problem size increases and the average cost calculated by the algorithm gets closer to that of …SMART as number of epochs used in the developed algorithm is increased. Show more

Keywords: Fuzzy approximation, ANFIS, reinforcement learning, SMDPs

DOI: 10.3233/IFS-141460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1733-1744, 2015

Authors: Haviez, Laura | Toscano, Rosario | El Youssef, Mohamad | Fouvry, Siegfried | Yantio, Ghislain | Moreau, Gilles

Article Type: Research Article

Abstract: In this paper it is shown that we can estimate the fretting wear evolution via an artificial neural network (ANN) model without making use of the back-propagation learning algorithm and without using any regularization method. This can be done by integrating in the ANN model all the available knowledge about the wear mechanism. This kind of model is referred to as a semi-physical neural model. One of the main advantages in building a semi-physical neural model is that its number of parameters is reduced compared with a standard ANN model. This is a very favourable property against the over-fitting inconvenience. …In addition, via appropriate nonlinear transformations, the semi-physical neural model can be rendered linear with respect to the parameters that are to be determined. Consequently, a simple least square approximation can be used to determine the unknown parameters. Show more

Keywords: Fretting Wear Estimation, Neural Network, Semi-Physical Neural Model

DOI: 10.3233/IFS-141461

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1745-1753, 2015

Authors: Lee, Wen-Chuan | Hong, Ching-Wen | Wu, Jong-Wuu

Article Type: Research Article

Abstract: Process capability analysis has been widely applied in the field of quality control to monitor the performance of industrial processes. In practice, process capability index Cpk is a popular means to assess target-the-best type quality performance. Normal distribution is an important assumption in process capability analysis. In product quality testing experiments, the experimenter may not always be in a position to observe the quality data of all the products (or items) put on test. Therefore, censored samples may arise in practice. Moreover, observations with coarse scales; measurement error that is not quantified accurately. Therefore, imprecise data also may arise …in practice. Our study purposes to utilize the process capability index Cpk in assessing the quality performance of products more generally and accurately. A new approach of analyzing normal, censored and imprecise data is proposed in our study. The new approach will apply a fuzzy statistical estimator of Cpk to develop a new fuzzy statistical hypothesis testing procedure under the normal distribution with the type II right censored sample, imprecise data and large sample. The new fuzzy statistical hypothesis testing procedure can handle normal, censored, imprecise and large sample quality data. Moreover, the purchasers can then employ the new fuzzy statistical hypothesis testing procedure to determine whether the quality performance of products adheres to the required level. The manufactures also can utilize the new fuzzy statistical hypothesis testing procedure to enhance product process capability. Show more

Keywords: Process capability analysis, Type II right censored sample, Normal distribution, Fuzzy statistical hypothesis testing

DOI: 10.3233/IFS-141463

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1755-1773, 2015

Authors: Ebonzo Menga, Angelo Dan | Lu, Jing | Liu, Xiaodong

Article Type: Research Article

Abstract: SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis is one of the most widely used strategic planning and decision making tool. However, it still has some structural problems such as the lack of prioritization of the alternatives, and too many extractable strategies. In this paper, we suggest a new approach to ranking the strategy alternatives via the SWOT analysis by making use of the Axiomatic Fuzzy Set (AFS) theory to find the best description of the alternatives and use the Evidential Reasoning (ER) approach in the light of AFS to rank the alternatives. The advantages of using the hybrid method (AFS …theory and ER approach) to rank the alternatives are that: arbitrary “values in between” of the Expected Utilities are avoided; Decision Makers (DMs) do not need to give subjective judgments to the values of the degree of belief but instead, degrees of belief are directly obtained from the database via AFS theory. A comparison analysis with previous methodologies is made, and it is shown than the proposed hybrid methodology provides a far higher flexibility and effectiveness. Show more

Keywords: SWOT analysis, alternative strategies, axiomatic fuzzy sets theory, evidential reasoning approach

DOI: 10.3233/IFS-141464

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1775-1784, 2015

Authors: Shankar, S. | Thangarasu, S.K. | Mohanraj, T. | Pravien, D.S.

Article Type: Research Article

Abstract: This paper presents a comparison of experimental results and a fuzzy rule based system model for calculating the cutting force in the turning operation. A full bridge dynamometer was used to measure the cutting forces over the mild steel work piece and Cemented Carbide Insert tool for different combinations of cutting velocity, feed rate and depth of cut. The rake angle, approach angle and nose radius of the cutting tool insert is kept constant throughout the experiment. This fuzzy model consists of 27 rules and Mamdani Max-min inference mechanism was used. The Taguchi designs of experiments were used to determine …the number of experiments. Also, an attempt had been made to analyze the influence of the parameters using the regression analysis which yields a maximum error of 3.214% at the time of prediction which was smaller. The experiments are planned based on Taguchi's design and the measured cutting forces were compared with the predicted forces in order to validate the feasibility of the proposed design. The percentage contribution of each process parameter had been analyzed using Analysis of Variance (ANOVA). Experimental results were compared with the regression analysis and predicted fuzzy model. The difference between experimental and predicted results was obtained as around 98.84%. Show more

Keywords: Full bridge dynamometer, cemented carbide tool, regression analysis, fuzzy logic, turning process

DOI: 10.3233/IFS-141465

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1785-1793, 2015

Authors: Gualtieri, Jean-Sébastien | Bisgambiglia, Paul-Antoine

Article Type: Research Article

Abstract: We are currently working on the realization of a PLS: Polyphony Learning Software tool within the framework of a pluridisciplinary project for promoting and preserving the Corsican culture. In this article we shall describe the different technical choices adopted so as to develop this learning tool based upon a gestural language. This software should enable a single singer to create polyphony. This is possible by replacing the other singers with singing voices. Our problematic is to associate artificial voices to each of the language gestures. This process has been broken down into several steps: defining a gestural language, gesture capture …and recognition, association of a singing voice. Show more

Keywords: Polyphony learning software, fuzzy inference system, recognition, polyphony

DOI: 10.3233/IFS-141466

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1795-1803, 2015

Authors: Vannucci, Marco | Colla, Valentina

Article Type: Research Article

Abstract: A novel approach for the adaptive tuning of recombination rates of genetic algorithm through a fuzzy inference system is proposed. The method exploits a set of features assessing the status of the optimization process and determined on the basis of the fitness of a representative subset of the population. This features, at each generation, are fed to a fuzzy system for adjusting the mutation and crossover rates of the genetic algorithm. The method has been tested on classical problems that are often used in literature for assessing optimization algorithms. The achieved results show that this procedure improves the performance of …the optimization process, by both speeding up the search, and avoiding the genetic algorithm to converge toward local minima. Show more

Keywords: Genetic algorithms, fuzzy logic, adaptation, recombination rates

DOI: 10.3233/IFS-141467

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 4, pp. 1805-1818, 2015