Journal of Intelligent & Fuzzy Systems - Volume 26, issue 1

Authors: Erdik, Tarkan

Article Type: Research Article

Abstract: Safe use of densely populated coastal zones depends on the performance of coastal structures against severe wave attack and strong currents. Economic and safe design of the crest height of these structures require accurate estimation of 2% wave run-up value on breakwater slope. Although, in practice, regression-based approach is widely-used, it is demonstrated herein that a set of restrictive assumptions hinder its use. As an alternative, Mamdani Fuzzy Logic model suggested with no restrictive assumptions. Hence, the goal is to provide an alternative approach that is better than the regression-based approach at estimating 2% wave run-up level. In order to …verify and compare the presented method's applicability, 261 irregular wave run-up data of Van der Meer and Stam are considered for impermeable, permeable and homogenous rubble mound structures. Finally, 13 unique prototype data of Van de Walle are employed to test the proposed model. It is demonstrated that Mamdani Fuzzy Logic model gives smaller error than the regression-based approach. Show more

Keywords: Artificial intelligence, Mamdani fuzzy approach, breakwaters, crest level approximation, 2% wave run-up

DOI: 10.3233/IFS-2012-0530

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 1-9, 2014

Authors: Mendi, Engin

Article Type: Research Article

Abstract: In this paper, we present a 3D face animation system rendered on mobile devices. The system automatically creates realistic facial animation from text input with emotion tags. First, an input string is converted into synthetic voice and phonetic information. Then, 3D head model performs facial movements synchronized to the speech. The proposed system offers an affordable quick solution for applications that require virtual actors speaking text in which human-machine interfaces on mobile devices can profit.

Keywords: 3D facial animation, text-to-visual speech synthesis, human-machine interfaces, rendering, mobile computing

DOI: 10.3233/IFS-120690

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 11-18, 2014

Authors: Hashemi, Farid | Kazemi, Ahad | Soleymani, Soodabeh

Article Type: Research Article

Abstract: This paper proposes a new integrated diagnostic system for islanding detection by means of an adaptive neuro-fuzzy inference system (ANFIS). Islanding detection and prevention are mandatory requirements for grid connected distributed generation (DG) systems. Several methods based on passive and active detection scheme have been proposed. While passive schemes have a large non detection zone (NDZ), the concern has been raised on active method due to their degrading power quality effect. Reliably detecting this condition is regarded by many as an ongoing challenge as existing methods are not entirely satisfactory. The main emphasis of the proposed scheme is to reduce …the NDZ to as close as possible and to keep the output power quality unchanged. In addition, this technique can also overcome the problem of setting the detection thresholds inherent in the existing techniques. This approach utilizes different parameters such as rate of change of frequency and rate of change of power and uses them as the input sets for training a neuro-fuzzy inference system for intelligent islanding detection. To validate the feasibility of this approach the method has been validated through several conditions and different loading, switching operation and network conditions. Simulation studies show that the ANFIS-based algorithm detects islanding situation more accurately than other algorithms and found to work effectively in the situations where other methods fail. Moreover, for those regions which are in need of a better visualization, the proposed approach would serve as an efficient aid such that the main power disconnection can be better distinguished. Show more

Keywords: Power system protection, distributed generation, islanding detection, non detection zone, rate of change of frequency, rate of change of active power, adaptive neuro fuzzy inference system

DOI: 10.3233/IFS-120711

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 19-31, 2014

Authors: Abbas, Mujahid | Turkoglu, Duran

Article Type: Research Article

Abstract: Existence of a fixed point for a fuzzy mapping satisfying a generalized contractive condition is proved. Our result, supported with an example, provide extension as well as substantial improvements of several well known results in the existing literature.

Keywords: Fuzzy mapping, fuzzy set, fuzzy fixed point

DOI: 10.3233/IFS-120712

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 33-36, 2014

Authors: Kara, Selin Soner | Cheikhrouhou, Naoufel

Article Type: Research Article

Abstract: Today, operational managers are experiencing difficulties in selecting the software that best suits their increasing number of requirements. These decision makers need to clarify what their needs are, what these packages offer and which software packages best fit their needs. Among the available tools, collaborative software is used to manage teams of people and different types of communication resources. This paper proposes a multi-criteria decision making technique for the selection of collaborative software. The technique is applied to a software company that develops business management solutions for Small and Medium sized Enterprises. The proposed group decision-making methodology is designed to …handle both quantitative and qualitative criteria. Criteria weights are calculated using a two-step multi-criteria decision making method: Fuzzy Analytical Hierarchy Process for the experts' and criteria weights, and Technique for Order Preference by Similarity to Ideal Solution for ranking the alternatives. Results show that the presented methodology reduces the uncertainty in decision-making and provides robust solutions. Show more

Keywords: Collaborative software, fuzzy AHP, group decision making, TOPSIS

DOI: 10.3233/IFS-120713

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 37-47, 2014

Authors: Firouzi, Mohsen | Shouraki, Saeed Bagheri | Afrakoti, Iman Esmaili Paeen

Article Type: Research Article

Abstract: Active Learning Method (ALM) is a powerful fuzzy soft computing tool, developed originally in order to promote an engineering realization of human brain. This algorithm, as a macro-level brain imitation, has been inspired by some behavioral specifications of human brain and active learning ability. ALM is an adaptive recursive fuzzy learning algorithm, in which a complex Multi Input, Multi Output system can be represented as a fuzzy combination of several Single-Input, Single-Output systems. SISO systems as associative layer of algorithm capture partial spatial knowledge of sample data space, and enable a granular knowledge resolution tuning mechanism through the learning process. …The knowledge in each sub-system and its effectiveness in the whole system would be extracted by Ink Drop Spread in brief IDS operator and consolidated using a Fuzzy Rule Base (FRB), in order to acquire expert knowledge. In this paper we investigate ALM as a conspicuous classifier in different types of classification problems. Also, a new ALM architecture to actively analyze ill-balanced image patterns is proposed. Different types of data sets are used as a benchmark, including a remote sensing image classification problem, to evaluate the ALM Classifier (ALMC). With active pattern generation ability and knowledge resolution tuning, ALMC has been distinguished from many conventional classification tools especially for complex structures and image patterns analysis. This work demonstrates that ALMC is a good noise robust and active classifier, which is adaptively adjusted through structural evolution and pattern evaluation mechanism. These remarkable capabilities, along with its straightforward learning process, make ALMC as a convenient soft computing tool to use in different types of low dimensional pattern recognition problems. Show more

Keywords: Active learning method, Adaptive neuro-fuzzy classifier, remote sensing image classification, radial base function network, Support vector machine

DOI: 10.3233/IFS-120714

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 49-62, 2014

Authors: Soleimani, Mohammad | Khoei, Abdollah | Hadidi, Khayrollah

Article Type: Research Article

Abstract: One of the active areas of fuzzy logic applications is control systems. In this paper presents a proposed Fuzzy Logic Controller (FLC) chip utilized a novel Membership Function Circuit (MFC) which can be made programmable. This membership function features of large dynamic range, high current driving, high noise immunity and is simply tunable by setting some voltages on IC pins. Each input of controller has five membership functions and output has seven singletons. A new structure for Min/Max operators, and also, a new current-mode divider circuit with very small area, very low power consumption and high speed and accurate are …presented, which are compatible to the proposed MFC, are also given. This controller is a general-purpose two-input one-output fuzzy controller that can be implemented in 0.08-mm2 in 0.35-μm CMOS technology (BSIM3v3). For general control tasks, input-output inference of FLC is voltage/voltage. The maximum delay in output of FLC is about 67-ns that correspond to 15-MFLIPS (Fuzzy Logic Inference per Second) and power consumption is 2.5-mW. Show more

Keywords: Fuzzy logic, fuzzy control, current-mode, min-max operator, fuzzifier, defuzzifier

DOI: 10.3233/IFS-120715

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 63-76, 2014

Authors: Shahsavari-Pour, Nasser | Tavakkoli-Moghaddam, Reza | Basiri, Mohammad-Ali

Article Type: Research Article

Abstract: Ranking of fuzzy numbers is one of the practicable operators, which plays an important role in fuzzy mathematical, decisions and engineering procedures. There is considerable work in ranking of fuzzy numbers that have been improved over time. However, some strong ranking methods need to calculate complex and lengthy mathematical calculations in their ordering processes. In this paper, we represent a novel ranking method of trapezoidal/triangular fuzzy numbers (TFNs) based on the Shadow length, which is simply coded in any programming language. On the other hand, many fuzzy numbers ranking methods give the same order for fuzzy numbers in any level …of manager's risk taking. So we insert the risk taking factor (RF) to order fuzzy numbers and provide a reasonable range of fuzzy numbers comparison through wide levels of this factor. Furthermore, we apply and compare several useful examples and ranking methods to depict the reasonable performance of our proposed method. Show more

Keywords: trapezoidal/triangular fuzzy number, fuzzy numbers ranking, Shadow method, risk taking factor

DOI: 10.3233/IFS-120716

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 77-89, 2014

Authors: Zhao, Chihang | Lian, Jie | Dang, Qian | Tong, Can

Article Type: Research Article

Abstract: In order to develop Human-centric Driver Fatigue Monitoring Systems (HDFMS) with aims to increase driving safety, an efficient combined features extraction from Curvelet transform and Gabor wavelet transform for fatigue expressions descriptions of vehicle drivers is proposed, and Random Subspace Ensemble (RSE) of Support Vector Machines (SVMs) with polynomial kernel as the base classifier is then exploited for classification of three predefined fatigue expressions classes, namely, awake expressions, moderate fatigue expressions, and severe fatigue expressions. The results of holdout and cross-validation experiments show that CF by RSE of SVMs with polynomial kernel outperforms other seven classifiers, i.e., Curvelet features by …SVMs classifier, Gabor features by SVMs classifier, CF by five individual SVMs classifiers. With CF and RSE of SVMs with polynomial kernel, the classification accuracies of drivers' fatigue expressions are over 90% in both of the holdout and cross-validation experiments, which show the proposed approach of combined features extraction and RSE of SVMs can be used for developing Human-centric Driver Fatigue Monitoring Systems to increase driving safety. Show more

Keywords: Fatigue expressions, curvelet transform, gabor transform, support vector machines, random subspace ensemble

DOI: 10.3233/IFS-120717

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 91-100, 2014

Authors: Qadri, Muhammad Yasir | McDonald Maier, Klaus D. | Qadri, Nadia N.

Article Type: Research Article

Abstract: Multicore architectures offer an amount of parallelism that is often underutilized, as a result these underutilized resources become a liability instead of advantage. Inefficient resource sharing on the chip can have a negative impact on the performance of an application and may result in greater energy consumption. A large body of research now focuses on reconfigurable multicore architectures in order to support algorithms to find optimal solutions for improved energy and throughput balance. An ideal system would be able to optimize such reconfigurable systems to a level that optimum resources are allocated to a particular workload and all the other …underutilized resources remain inactive for greater energy savings. This paper presents a fuzzy logic based reconfiguration engine targeted to optimize a multicore architecture according to the workload requirements for optimum balance between power and performance of the system. The proposed fuzzy logic reconfiguration engine is designed around a 16-core SCMP architecture comprising of reconfigurable cache memories, power gated cores and adaptive on-chip network routers for minimizing leakage energy effects for inactive components. A coarse grained architecture was selected for being able to reconfigure faster, thus making it feasible to be used for runtime adaptation schemes. The presented architecture is analyzed over a set of OpenMP based parallel benchmarks and results show significant energy savings in all cases. Show more

Keywords: Energy efficiency, Fuzzy logic, reconfiguration, Multicore processing

DOI: 10.3233/IFS-120718

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 101-113, 2014