Journal of Intelligent & Fuzzy Systems - Volume 30, issue 3

Authors: Motameni, Homayun | Peykar, Alieh

Article Type: Research Article

Abstract: Given the ability of fuzzy systems to make decisions in uncertainties such as morphology, and the huge number of studies conducted on morphology, this study first suggests a fuzzy morphology; then, it discusses the effectiveness of types of N-gram labeling methods to identify the role of words in Persian compounds. To find the optimal labeling, then, a new hybrid method is expressed for N-gram labeling. In relation to compound sentences, two independent roles including subject, governing predicate, predicate, object and complement and dependent roles including noun, adverb, governing genitives, genitives, bending, retroactive, apposition, exclamation and annunciator are studied. To compare …the success rate of the proposed fuzzy method, existing HMM (hidden Markov model) is studied to identify the role of words in three different label types. The results of this comparison showed that the success rates of hybrid labeling and Bi-gram labeling are closed in both models. Thus, these two methods have been successful in both morphological models compared to Uni-gram labeling. It is worth noting, the highest success rate was related to fuzzy morphology and Bi-gram labeling. Show more

Keywords: Fuzzy System, HMM, combine, independent roles, dependent roles

DOI: 10.3233/IFS-151865

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1567-1580, 2016

Authors: Singh, Sukhpal | Chana, Inderveer

Article Type: Research Article

Abstract: In Cloud computing, data centers gain popularity as an effective platform for scheduling of resources and hosting cloud applications. However, tremendous amount of energy is consumed by these data centers which leads to high operational costs and contributes towards carbon footprints to the environment. Therefore, there is need of energy aware cloud based framework which schedules computing resources automatically by considering energy consumption as a QoS parameter itself. In this paper, we present fuzzy logic based energy-aware autonomic resource scheduling framework for cloud for energy efficient scheduling of cloud computing resources in data centers. We have evaluated the proposed framework …in CloudSim based simulation environment and real cloud environment. The experimental results show that the proposed framework performs better in terms of resource utilization and energy consumption along with other QoS parameters. Show more

Keywords: Autonomic cloud computing, energy, resource scheduling, fuzzy logic, self-optimization, green computing

DOI: 10.3233/IFS-151866

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1581-1600, 2016

Authors: Shanghooshabad, Ali Mohammadi | Abadeh, Mohammad Saniee

Article Type: Research Article

Abstract: In the paper we will try to generate fuzzy rule based systems (FRBSs) that follow three objectives: accuracy, interpretability and robustness. Accuracy is based on the Number of Patterns that are Correctly Classified (NCP), interpretability is measured as the Number of Rules (NR) and Sum of the Rules Length (SRL) and Robustness is measured as Sum of the accuracy, NR and SRL Standard Deviations (Sum of SDs) in successive runs. The algorithms that have high quality results with low SDs and in each run, the output is not being different, are called robust algorithms. Our algorithm consists of two stages …based on the Krill Herd (KH) evolutionary algorithm; in the first stage the candidate rules are generated intelligently so in the second stage, those rules will be selected that get us closer to our objectives. Stage 2 of our algorithm can be used as a post processing algorithm on other algorithms and converts those to robust algorithms. The results show that, our algorithm has zero SDs with high accuracy and we have been successful in improving those three objectives that were in conflict. Show more

Keywords: Medical data mining, robust evolutionary algorithms, krill herd, fuzzy rule based system, fuzzy rule learning

DOI: 10.3233/IFS-151867

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1601-1612, 2016

Authors: Jun, Young Bae | Song, Seok-Zun | Muhiuddin, G.

Article Type: Research Article

Abstract: The notion of a hesitant fuzzy semigroup with a frontier is introduced, and several properties are investigated. Characterizations of a hesitant fuzzy semigroup with a frontier are considered, and a condition for a special set to be a subsemigroup is provided. The hesitant union and hesitant intersection of two hesitant fuzzy semigroups with a frontier are dealt with, and the hesitant fuzzy pre-image and hesitant fuzzy image of a hesitant fuzzy semigroup with a frontier under the homomorphism are discussed.

Keywords: Hesitant fuzzy semigroup (with a frontier), hesitant fuzzy pre-image, hesitant fuzzy image

DOI: 10.3233/IFS-151869

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1613-1618, 2016

Authors: Luo, Minxia | Cheng, Ze | Wu, Jiao

Article Type: Research Article

Abstract: In this paper, the interval-valued triple I algorithms based on two inference models, i.e. fuzzy modus ponens and fuzzy modus tollens, are extended to the (1,2,1)-type universal triple I algorithms. The corresponding (1,2,1)-type universal triple I solutions are given. Moreover, the robustness of interval-valued (1,2,1)-type universal triple I algorithms are studied. As the corollaries of the main results, the sensitivity of [α , β ]-(1,2,1)-type universal triple I solutions based on interval-valued Lukasiewicz implication and R 0 implication are given. In particularly, the sensitivity of α -(1,2,1)-type universal triple I methods based on classical sets are given.

Keywords: Interval-valued fuzzy inference, (1,2,1)-type universal triple I method, the sensitivity of the interval-valued fuzzy inference, robustness

DOI: 10.3233/IFS-151870

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1619-1628, 2016

Authors: Doagou-Mojarrad, H. | Rastegar, H. | Gharehpetian, G.B.

Article Type: Research Article

Abstract: In this paper, an interactive fuzzy satisfying method based on fuzzy adaptive chaotic binary particle swarm optimization (FACBPSO) algorithm is proposed to investigate the multi-objective Generation and Transmission Expansion Planning (G-TEP). The objective functions of the G-TEP problem, which are modeled by fuzzy sets, present the total investment/operation cost and the total pollutant emission. In modern power systems, the necessity of considering the wind/solar energy resources in Generation Expansion Planning (GEP) studies is important. In addition, HVDC links, transmitting renewable resource power from remote sites, should be considered in TEP problem. The use of the wind/solar energy due to the …uncertainty of their generation and the integration of HVDC links would consequently impose more complexity to solution of the G-TEP problem. In this paper, the proposed algorithm is tested on an IEEE test system based on economic and environmental considerations to generate an optimal expansion plan. Show more

Keywords: Stochastic modeling, Generation and Transmission Expansion Planning, HVDC links, Wind/solar energy resources, fuzzy adaptive PSO, interactive fuzzy satisfying method

DOI: 10.3233/IFS-151871

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1629-1641, 2016

Authors: Zhang, Lingyu | Tao, Bairui

Article Type: Research Article

Abstract: Ontology integration is an important work when integrating information from heterogeneous ontologies into an ontology. The existing methods about ontology integration cannot effectively make full use of non-1-1 mappings, which are very common in the real world. Furthermore, these methods only stated that the concept-pairs with mappings should be integrated, but not gave the specific operations for it. Therefore, these methods cannot describe a complete framework for ontology integration. To this end, this paper proposes a framework for Ontology Integration based on Genetic Algorithm, called OI-GA. During the process of integrating ontologies, OI-GA firstly creates mappings between them based on …similarity measures. Next, OI-GA finds out all the non-1-1 mappings from mappings, and provides an evolutionary method to extract 1-1 mappings from them. Finally, all the concepts belonging to different ontologies are integrated into a new knowledge base called integrated ontology. Experimental results indicate that OI-GA performs encouragingly well in the optimization of mapping set as well as in the integration of ontologies from the real world. Show more

Keywords: Ontology integration, mapping, genetic algorithm, evolutionary method

DOI: 10.3233/IFS-151872

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1643-1656, 2016

Authors: Shi, Hui-Xian | Li, Yong-Ming

Article Type: Research Article

Abstract: In the present paper, the concepts of characters as well as the least characters for LTL (Linear Temporal Logic) formulae are introduced. It is pointed out that those LTL formulae with characters can always be checked within finite steps during model checking even in some cases when the underlying transition system contains infinite states. What is more, the class of LTL formulae with characters can be characterized by full LTLn , the bounded case for LTL. Meanwhile, two types of temporal normal form for LTL formulae are proposed. A necessary and sufficient condition is given in which an LTL …formula has an equivalent formula in temporal normal form. Show more

Keywords: Linear Temporal Logic, transition system, character, temporal normal form

DOI: 10.3233/IFS-151874

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1657-1662, 2016

Authors: Phu, Nguyen Dinh | Tri, Phan Van

Article Type: Research Article

Abstract: In this work we consider the fuzzy dynamic programming problems. For this purpose, using the generalized Hukuhara differentiability for fuzzy functions, new concepts, for example: the fuzzy product, the fuzzy collocation and the Bellman’s principle, we have the neccesary and sufficient conditions.

Keywords: Fuzzy number, fuzzy Hausdrorff metric space, generalized Hukuhara differentiability, the fuzzy dynamic programming problems, Bellman’s principle

DOI: 10.3233/IFS-151875

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1663-1674, 2016

Authors: Yan, Gaowei | Ji, Shanshan | Xie, Gang

Article Type: Research Article

Abstract: Considering the strong uncertainty in ball mills, cloud model which combines fuzziness and randomness together and has the ability of processing uncertainty, is introduced. The paper proposes a novel soft sensor based on uncertainty reasoning of cloud model to improve the accuracy and reliability of fill level measurement. At first, power spectral densities of the vibration signals are extracted by Welch’s method and the features are obtained by summing the energy of a wide frequency band. Then backward cloud generator algorithm is used to represent numerical characteristics of antecedent clouds under different fill levels, and the corresponding consequent clouds are …given according to the fill level information. Thus, the rule base is built and the uncertainty reasoning based on cloud model is realized. As it is difficult to obtain data set continuously and accurately in practical industry fields, virtual cloud is employed to deal with the problem of sparse rule base in the case of insufficient samples. The experimental results show that the accuracy of proposed method can meet the requirements of field measurement applications. In addition, the method based on virtual cloud is more accurate and robust compared with other methods in the case of insufficient samples. Show more

Keywords: Ball mill fill level, soft sensor, vibration signals, cloud model, uncertainty reasoning

DOI: 10.3233/IFS-151876

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1675-1689, 2016