Journal of Intelligent & Fuzzy Systems - Volume 32, issue 6

Authors: Nazari-Shirkouhi, Salman | Miri-Nargesi, Sina | Ansarinejad, Ayyub

Article Type: Research Article

Abstract: Many companies outsource their information systems (ISs) to share risk, reduce cost and achieve high level of performance quality. One of the most important steps in IS outsourcing is selection of the best appropriate candidate information systems for outsourcing. To address such problem, the multiple-criteria decision making (MCDM) methods could be applied. Therefore two MCDM approaches consisting of the integrated fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) for evaluating and selecting the appropriate Information System Project (ISP) can be employed. The proposed method has been applied in an actual case, …an online book store in Iran. The FAHP is used to analyze the structure of the outsourcing problem and determine weights of the criteria, and FTOPSIS method is used for final ranking of ISPs. Finally to validate the obtained results, a sensitivity analysis is carried out. Show more

Keywords: Information system outsourcing, multiple-criteria decision making, FAHP, FTOPSIS, sensitivity analysis

DOI: 10.3233/JIFS-12495

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 3921-3943, 2017

Authors: Vashisth, Pooja | Khurana, Purnima | Bedi, Punam

Article Type: Research Article

Abstract: Recommender Systems (RSs) are largely used nowadays to generate interest items or products for web users of diverse nature. Therefore, this work focuses on using fuzzy logic to accommodate diversity and uncertainty in user choices and interest. This would help in generating better recommendations with different tastes that correspond to different interest choices of the user. In this paper, a fuzzy hybrid multi-agent recommender system is designed and developed. The novelty of our approach is the use of interval type-2 fuzzy sets to create user models capable of capturing the inherent ambiguity of human behavior related to diverse users’ tastes. …In the due course, we also extended an existing, well known hybrid recommendation method, by integrating the proposed fuzzy approach into the recommendation process. As a result, a new RS approach was developed, which was capable of improving the prediction accuracy of system and at the same time reducing errors by being able to extract more information from the available dataset. Experimental study and analysis was conducted using two case studies namely book purchase and shopping women apparels. As a result, the proposed recommendation approach was found to perform considerably well as compared to its counterparts, even under data sparsity conditions. Show more

Keywords: Keyword recommendation, preferences, interval type-2 fuzzy sets, personalization, user modeling

DOI: 10.3233/JIFS-14538

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 3945-3960, 2017

Authors: Bakhtiarifar, Mohammad Hasan | Amiri, Amirhossein | Alaeddini, Adel

Article Type: Research Article

Abstract: Economic-statistical design of control charts has been extensively discussed in the recent literature of Statistical Process Control (SPC). Meanwhile, X ¯ control charts have received more attention due to their simplicity and vast applications. However, due to the effects of multiple factors in real applications, it is difficult to specify accurate values for the economic parameters such as cost and profit, which are associated with the design of X ¯ chart. Hence, It is necessary to enter uncertainty parameters into the control chart design model. In this paper, …an economic-statistical design of X ¯ Shewhart control chart with fuzzy parameters has been studied. Two modeling methods have been proposed and then Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm II (NSGA II) are applied to optimize the multi-objective model with the two aggregated and non-aggregated approaches. A numerical example is given for validation of the proposed models and solution algorithms. Finally, some sensitivity analyses are conducted. Show more

Keywords: Statistical Process Control (SPC), fuzzy parameters, economic-statistical design, Shewhart control chart, Genetic algorithm (GA), Non-dominated sorting genetic algorithm II (NSGA II)

DOI: 10.3233/JIFS-151097

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 3961-3971, 2017

Authors: Yang, Hong | Liu, Xiaodong | Zhang, Le

Article Type: Research Article

Abstract: This paper deals with observer-based tracking controller design for time-delay switched fuzzy system with unmeasurable premise variables. A switched fuzzy system, which integrates fuzzy and switching features, can describe continuous and discrete modes and complex nonlinear phenomena of objective reality as well as their coupling and interactions. A fuzzy state observer is investigated for estimating the unmeasured states and unmeasurable premise variables. The stability and the switching control law based on measured state of the dynamic errors system are then analyzed by multiple Lyapunov function approach. In this study, the H∞ tracking control problem of a time-delay switched fuzzy …system is solvable, which some sub time-delay fuzzy systems are allowed to be unstable. The variation-of-constants formula is used to overcome the difficulties caused by the estimation error and exotic disturbance. Finally, a competitive experiment on an R/C hovercraft is given to demonstrate the effectiveness of the proposed control schemes. Show more

Keywords: Switched fuzzy system, time-delay, unmeasurable premise variables, tracking control, observer

DOI: 10.3233/JIFS-151256

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 3973-3985, 2017

Authors: Kianian, Sahar | Khayyambashi, Mohammad Reza | Movahhedinia, Naser

Article Type: Research Article

Abstract: Finding community structures in online social networks is an important methodology for understanding the internal organization of users and actions. Most previous studies have focused on structural properties to detect communities. They do not analyze the information gathered from the posting activities of members of social networks, nor do they consider overlapping communities. To tackle these two drawbacks, a new overlapping community detection method involving social activities and semantic analysis is proposed. This work applies a fuzzy membership to detect overlapping communities with different extent and run semantic analysis to include information contained in posts. The available resource description format …contributes to research in social networks. Based on this new understanding of social networks, this approach can be adopted for large online social networks and for social portals, such as forums, that are not based on network topology. The efficiency and feasibility of this method is verified by the available experimental analysis. The results obtained by the tests on real networks indicate that the proposed approach can be effective in discovering labelled and overlapping communities with a high amount of modularity. This approach is fast enough to process very large and dense social networks. Show more

Keywords: Community detection, semantic analysis, social network, fuzzy relation model, overlapping communities

DOI: 10.3233/JIFS-151276

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 3987-3998, 2017

Authors: Cai, Fei | Chen, Honghui

Article Type: Research Article

Abstract: Query completion service, normally known in the form of query auto completion (QAC) and widely provided by common search engines, assists users to formulate their queries after only typing few keystrokes. Previous work on QAC basically ranks query candidates according to their query popularity which is collected from the search logs, ignoring the internal semantic similarity between terms inside a query. However, we argue semantically related terms are apt to be combined when generating a query. In addition, as users often engage in QAC at word boundary (i.e., after typing a full word), we suppose that the time-aware popularity of …the first word in a query candidate could affect the ranking of QAC candidates. Hence, based on the Markov assumption, we propose a new QAC ranking method, which models the QAC engagement as a Markov Chain and takes the semantic similarity between query terms into account. We contrast our proposed model with the traditional query popularity-based QAC approaches and verify its effectiveness in terms of Mean Reciprocal Rank (MRR). The experimental results show that our model significantly outperforms the baselines, achieving an average MRR improvement around 4% over the baselines. Show more

Keywords: Information retrieval, query completion, query suggestion, semantics, query formulation

DOI: 10.3233/JIFS-151404

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 3999-4008, 2017

Authors: Rao, Congjun | Xiao, Xinping | Xie, Ming | Goh, Mark | Zheng, Junjun

Article Type: Research Article

Abstract: Under the development mode of low carbon economy, selecting the best low carbon supplier is the basis and prerequisite for establishing low carbon supply chain, and is the inevitable choice to achieve sustainable development for enterprises. In this paper, we investigate the problem of low carbon supplier selection in the multi-source and multi-attribute procurement. Concretely, we establish a new evaluation index system of low carbon supplier selection based on cost, low carbon, quality and service capacity. Then we present a multi-attribute decision making method for low carbon supplier selection based on a linguistic 2-tuple VIKOR method. In this proposed decision …method, the hybrid attribute values (the real numbers and linguistic fuzzy variables coexist) are transformed into linguistic 2-tuples, and a ranking method based on an extended VIKOR method is then presented to rank all alternative suppliers. We also give an application example to highlight the implementation, availability, and feasibility of the proposed decision making method. Show more

Keywords: Low carbon economy, low carbon supplier selection, multi-attribute decision making, linguistic 2-tuple, extended VIKOR method

DOI: 10.3233/JIFS-151813

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 4009-4022, 2017

Authors: Yu, Miao

Article Type: Research Article

Abstract: In recent years, the electronic information and network technology has developed rapidly, meanwhile, E-commerce has been widely applied in society. Especially the online shopping, relying on its rich products, low price, no time and geographical restrictions and several other distinctive characteristics, which has absorbed attentions of many consumers. In recent years, China’s online retail market has seen a big growth. The market share of e-commerce has gradually increased and become a mainstay of China’s e-commerce development. However, with the fast growth of e-commerce, consumers’ requirements for enterprise service quality is also getting higher and higher. Logistics services is considered to …be one of the three main inhibitions of e-commerce and improve logistics service quality has gradually become an important way of e-commerce enterprises to obtain competitive advantage. At present, the research on how to evaluate the quality of e-commerce logistics services has not yet formed a complete and scientific theoretical system and method. In this paper, we have proposed the induced hesitant fuzzy uncertain linguistic Einstein correlated average (IHFULECA) operator. Then, we used the IHFULECA operator to design the multiple attribute decision making problems to estimate the E-commerce logistics service quality. At last, an example is given to shown the effectiveness of the proposed method. Show more

Keywords: Assessment, hesitant fuzzy uncertain linguistic values, induced hesitant fuzzy uncertain linguistic Einstein correlated average (IHFULECA) operator, E-commerce logistics service quality

DOI: 10.3233/JIFS-152069

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 4023-4029, 2017

Authors: Gollou, Abbas Rahimi | Ghadimi, Noradin

Article Type: Research Article

Abstract: In this paper, a new feature selection and forecast engine is presented for day ahead prediction of electricity prices, which are so valuable for both producers and consumers in the new competitive electric power markets. In a competitive electricity market, forecast of energy prices is a key information for the market participants. However, price signal usually has a complex behavior due to its nonlinearity, non-stationary, and time variance. Also, an appropriate feature selection is crucial for accurate forecasting. In this paper, a two-step approach that identifies a set of candidate features based on the data characteristics proposed and then selects …a subset of them using correlation and instance-based feature selection methods, applied in a systematic way. Then, a combination of wavelet transform (WT) and a hybrid forecast method is presented based on neural network (NN) and an optimization algorithms. The proposed method is examined on PJM electricity market and compared with some of the most recent price forecast methods. These comparisons illustrate effectiveness of the proposed strategy. Show more

Keywords: Neural network, price forecast, feature selection, hybrid forecast engine

DOI: 10.3233/JIFS-152073

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 4031-4045, 2017

Authors: Modhej, D. | Sanei, M. | Shoja, N. | HosseinzadehLotfi, F.

Article Type: Research Article

Abstract: The present paper is an attempt to integrate inverse Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN) for a large dataset with multiple Decision Making Units (DMUs). The purpose of this study is to determine the best possible values of inputs for a large number of DMUs when their output levels are changed and their efficiency values remain unchanged. When the ANN is used to develop inverse DEA, it is not necessary to solve the inverse DEA model for every single DMU. Therefore, this approach can save the computer’s memory and the CPU time especially for very large scale …datasets. To illustrate the ability of the proposed methodology, a set of 600 Iranian bank branches is used. Show more

Keywords: Artificial neural network, data envelopment analysis, inverse optimization, efficiency, resource allocation

DOI: 10.3233/JIFS-152271

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 4047-4058, 2017