Journal of Intelligent & Fuzzy Systems - Volume 26, issue 6

Authors: Mollaiy-Berneti, Shahram

Article Type: Research Article

Abstract: Multiphase flow meters (MFMs) which measure three-phase oil-gas-water flow rates, are being utilized to make available, quick and accurate well test data in different oil production applications, like in remote or unmanned locations, topside and subsea applications. Data acquisition and production monitoring of the wells are done discretely by conventional MFMs, due to radioactive sources and unmanned location due to wells far distance. This study presents the development of committee machine based soft sensor (CMSS), an alternative way to the conventional MFMs. The proposed CMSS combines the results of linear and nonlinear auto-regression exogenous input (ARX/NARX), artificial neural network (ANN) …and adaptive neuro-fuzzy inference system (ANFIS) for overall oil flow rate prediction of the wells, on the basis of available temperature and pressure measurements of lines. Each ensemble member has a weight factor which is derived in two ways including simple averaging and weighted averaging. In the weighted averaging method, the optimal combination of the weights is obtained by a novel optimization based method called imperialist competitive algorithm (ICA). Experiments on data set of 31 wells in one of the northern Persian Gulf oil fields of Iran proved the effectiveness of the proposed ICA optimized CMSS with an improved accuracy over the individual experts. Show more

Keywords: Multiphase flow meter, soft sensor, committee machine, imperialist competitive algorithm, ARX, NARX, ANN, ANFIS

DOI: 10.3233/IFS-130941

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2719-2729, 2014

Authors: Ghosh, Anupam | De, Rajat K.

Article Type: Research Article

Abstract: In this article, we propose a methodology for identifying the interactions among the genes in terms of dependencies (named as gene–gene interaction) that have altered quite significantly from normal stage to diseased stage with respect to their expression patterns. This idea leads to predict the disease mediating genes along with their altered interactions. The proposed methodology involves measuring information content of individual genes using fuzzy entropy, conditional fuzzy entropy of a gene on another, dependencies (interactions) of a pair of genes in both normal and diseased states, detecting the dependencies being deviated from normal to carcinogenic state and finally identifying …the influential genes from altered dependencies. Thus the gene–gene interactions for normal state and diseased state are represented separately by the gene dependency networks (GDN). The altered interactions among the genes have been represented using a network, called altered gene dependency network (AGDN), in which each node represents a gene and a directed edge signifies altered dependency between a pair of nodes (genes). The methodology has been demonstrated on five gene expression data sets dealing with human lung cancer, colon cancer, sarcoma, breast cancer and leukemia. The results are appropriately validated, in terms of gene–gene interactions, using biochemical pathways, t-test, p-value, NCBI database and earlier investigations in terms of gene regulation. We have also used sensitivity to validate the results. For a comparative study, we have used some existing association rule mining algorithms and frequent pattern mining algorithms like Fuzzy Cluster-Based Association Rules, Apriori, T-Apriori in terms of gene–gene interactions. In addition, we have implemented Significance Analysis of Microarray, Signal-to-Noise Ratio, Neighborhood analysis, Bayesian regularization and frequent pattern mining algorithms for a comparison with AGDN in terms of ability to identify the important genes mediating the cancers. Show more

Keywords: Gene dependency networks, altered gene dependency networks, lung cancer, colon cancer leukemia, sarcoma, breast cancer, t-test, p-value

DOI: 10.3233/IFS-130942

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2731-2746, 2014

Authors: Mon, Yi-Jen | Lin, Chih-Min

Article Type: Research Article

Abstract: The e-puck™ mobile robot is used and an intelligent obstacle avoidance algorithm is developed in this paper. The image data are processed by edge detection method. By using the recurrent fuzzy neural network (RFNN), the horizontal edge (HE) and vertical edge (VE) are feed into RFNN to train the control rules such as to control the right and left wheels of e-puck robot to avoid obstacles. The good control performances and effectiveness are demonstrated by the simulations of Matlab™ and Webots™; meanwhile, the empirical tests are also implemented to verify these performances.

Keywords: Recurrent fuzzy neural network (RFNN), mobile robot control, e-puck, webots, image processing

DOI: 10.3233/IFS-130943

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2747-2754, 2014

Authors: Huang, Qingmin | Chen, Ye-Hwa | Zhong, Zhihua

Article Type: Research Article

Abstract: The problem of motion control for constraint-following for uncertain mechanical systems is considered. The uncertainty in the system is (possibly) fast time-varying but is assumed to be bounded. Based on a fuzzy description of the uncertainty bound, we propose an adaptive robust control. The control is deterministic and is not if-then rule-based. An optimal design problem associated with the control is formulated, which allows us to choose the optimal gain for the adaptive law. The performance of the resulting controlled system is both deterministically guaranteed and fuzzily-optimized.

Keywords: Mechanical system, constraint, adaptive robust control, optimal design

DOI: 10.3233/IFS-130944

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2755-2769, 2014

Authors: Ghazanfari, Behzad | Mozayani, Nasser

Article Type: Research Article

Abstract: Nash Q-learning and team Q-learning are extended versions of reinforcement learning method for using in Multi-agent systems as cooperation mechanisms. The complexity of multi-agent reinforcement learning systems is extremely high thus it is necessary to use complexity reduction methods like hierarchical structures, abstraction and task decomposition. A typical approach for the latter to define subtasks is based on extracting bottlenecks. In this paper, bottlenecks are automatically extracted to create temporally extended actions which are in turn added to available agent's actions in cooperation mechanisms of multi-agent systems. The updating equations of team Q-learning and Nash Q-learning are extended in such …a way to involve temporally extended actions. In this way the performance of learning in team Q-learning and Nash Q-learning is considerably increased. The experimental results show an interesting improvement in the process of learning of cooperation mechanisms being augmented by extracted temporally actions in multi-agent problems. Show more

Keywords: Reinforcement learning, bottlenecks, clustering, options, hierarchical reinforcement learning

DOI: 10.3233/IFS-130945

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2771-2783, 2014

Authors: Zhao, Tao | Xiao, Jian | Ding, Jialin | Chen, Peng

Article Type: Research Article

Abstract: Traditional rough sets only could handle the datasets with discrete attributes, and have difficulty in handling real-valued attributes. The fuzzy rough set model which could deal with real-valued datasets has been introduced. However, fuzzy rough sets are sensitive to misclassification and perturbation. The variable precision fuzzy rough set model was introduced to handle datasets with misclassification and perturbation, but it could not effectively handle highly uncertain data. Interval type-2 fuzzy rough set model is a powerful tool to handle highly uncertain data. However, interval type-2 fuzzy rough set model is sensitive to misclassification. In this paper, the concept of variable …precision interval type-2 fuzzy rough sets (VPI2FRS) by combining variable precision fuzzy rough sets and interval type-2 fuzzy rough sets is introduced. Furthermore, a new attribute reduction approach within VPI2FRS framework is developed. In the end, we by experiments demonstrate the feasibility and effectiveness of the proposed reduction algorithm. Show more

Keywords: Interval type-2 fuzzy sets, rough sets, variable precision rough sets, variable precision interval type-2 fuzzy rough sets, attribute reduction

DOI: 10.3233/IFS-130946

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2785-2797, 2014

Authors: Sun, Wei | Ma, Tiannan

Article Type: Research Article

Abstract: Distribution network structure optimization is the important part of city network planning; it directly affects the reliability and safety of the electric operation. In order to optimize the traditional ant colony algorithm in distribution network structure optimization, this paper proposes a improved algorithm to solve the problems, such as long time calculating, system premature stagnation, invalid searching and so on. Based on traditional ant colony algorithm, this paper improves it by optimizing transition probability and volatile factor. In the design of transition, the gang control will be realized between two parameters α, β and Maximum iterating times Nmax ; In …the improvement of the volatile factor, the adaptability will be enhanced. Through the verification analysis of specific example, the results show that improved ant colony algorithm, compared with basic ant colony algorithm, increases the ability of global searching and constringency and accelerates the calculation speed of the algorithm. The modified algorithm is feasible and effective. Show more

Keywords: Distribution network structure optimization, power network operation, ant colony algorithm, volatile factor, global searching

DOI: 10.3233/IFS-130947

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2799-2804, 2014

Authors: Ezhil Vignesh, K. | Dora Arul Selvi, B.

Article Type: Research Article

Abstract: Nowadays, several methods are discovered for providing an efficient and an undisturbed power supply to the customers. This process starts at the generating station which mainly deals with Optimal Power Flow (OPF) method. The OPF method is an important method used to increase the power flow between the buses in a power system. The OPF deals with finding an optimal operating point of a power system that minimizes the cost function in terms of generation cost or transmission loss. The goal of OPF is to find the optimal settings of a given power system network that optimizes a certain objective …function while satisfying its power flow equations, system security, and equipment operating limits. FACTs controllers can also be used to increase the power flow between the buses by connecting them at suitable places in the transmission line. In this paper, a hybrid technique and ANN based OPF with UPFC is proposed. The proposed hybrid technique combines both the PSO and BBO algorithm. The optimal location of UPFC is determined by ANN. The proposed OPF technique tested with IEEE 30 bus system and the optimal power flow is analyzed. Show more

Keywords: OPF, FACTs, UPFC, hybrid technique, PSO, BBO, ANN, fuel cost, emission, power loss

DOI: 10.3233/IFS-130948

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2805-2815, 2014

Authors: Kavousi-Fard, Abdollah | Abbasi, Alireza | Baziar, Aliasghar

Article Type: Research Article

Abstract: This paper proposes a novel adaptive modification approach based on harmony search algorithm (HS) to solve the multi-objective environmental economic dispatch problem. The proposed algorithm makes use of adaptive formulations to update the adjusting parameters of HS including the pitch adjusting and bandwidth parameters and the harmony memory consideration rate during the optimization process. Meanwhile, a useful modification is proposed to improve the variety of the harmony population effectively. In order to handle both the cost and emission objective functions, the ideas of trapezoidal fuzzy membership function and weighting factor are employed. The satisfying performance of the proposed method is …examined through the IEEE standard test system. Show more

Keywords: Environmental economic dispatch (EED), adaptive modified harmony search (AMHS), fuzzy membership function

DOI: 10.3233/IFS-130949

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2817-2823, 2014

Authors: Ghodrati Amiri, Gholamreza | Amiri, Mohamad Shamekhi | Tabrizian, Zahra

Article Type: Research Article

Abstract: This paper proposes ground-motion prediction equations(GMPEs) for the horizontal component of earthquake in Iranian plateau. These equations present the velocity and acceleration response spectra at 5% damping ratio as continuous period functions, within range of 0.1 to 4 seconds. So far many equations have been presented and the recent suggested proportions are functions of several parameters. In this research, due to easy usage and lack of information in Iran, only the magnitude of earthquake, the distance between earthquake source and the location and the ground type are used as important factors. Iranian plateau is divided into two zones: Alborz-Central Iran …and Zagros, each of which is divided into rock and soil region according to the ground type. Regarding the fact that the occurred and reported earthquakes in Iran are shallow, surface wave magnitude (Ms) is used in this study. Moreover, hypocentral distance is considered as distance between the earthquake source and the location. To obtain the velocity and acceleration response spectra, a Gene Expression Programming(GEP) algorithm is used which utilizes no constant regression model and the model is acquired smartly as a continuous period function. The consequences show a consistency with high proportionality coefficient among the observed and anticipated results. Show more

Keywords: Ground-motion prediction equation, gene expression programming, Iran, rock, soil

DOI: 10.3233/IFS-130950

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2825-2839, 2014