Journal of Intelligent & Fuzzy Systems - Volume 41, issue 6

Authors: Raipurkar, Abhijeet R. | Chandak, Manoj B.

Article Type: Research Article

Abstract: A query application for On-Line Analytical Processing (OLAP) examines various kinds of data stored in a Data Warehouse (DW). There have been no systematic studies that look at the impact of query optimizations on performance and energy consumption in relational and NoSQL databases. Indeed, due to a lack of precise power calculation techniques in various databases and queries, the energy activity of several basic database operations is mostly unknown, as are the queries themselves, which are very complicated, extensive, and exploratory. As a result of the rapidly growing size of the DW system, query response times are regularly increasing. To …improve decision-making performance, the response time of such queries should be as short as possible. To resolve these issues, multiple materialized views from individual database tables have been collected, and queries have been handled. Similarly, due to overall maintenance and storage expenses, as well as the selection of an optimal view set to increase the data storage facility’s efficacy, materializing all conceivable views is not viable. Thus, to overcome these issues, this paper proposed the method of energy-aware query optimization and processing, on materialized views using enhanced simulated annealing (EAQO-ESA). This work was carried out in four stages. First, a Simulated Annealing (SA) based meta-heuristic approach was used to pre-process the query and optimize the scheduling performance. Second, the optimal sets of views were materialized, resulting in enhanced query response efficiency. Third, the authors assessed the performance of the query execution time and computational complexity with and without optimization. Finally, based on processing time, efficiency, and computing cost, the system’s performance was validated and compared to the traditional technique. Show more

Keywords: Simulated annealing, EAQO-ESA, materialized view selection, OLAP queries

DOI: 10.3233/JIFS-202821

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6191-6205, 2021

Authors: Alsayadi, Hamzah A. | Abdelhamid, Abdelaziz A. | Hegazy, Islam | Fayed, Zaki T.

Article Type: Research Article

Abstract: Arabic language has a set of sound letters called diacritics, these diacritics play an essential role in the meaning of words and their articulations. The change in some diacritics leads to a change in the context of the sentence. However, the existence of these letters in the corpus transcription affects the accuracy of speech recognition. In this paper, we investigate the effect of diactrics on the Arabic speech recognition based end-to-end deep learning. The applied end-to-end approach includes CNN-LSTM and attention-based technique presented in the state-of-the-art framework namely, Espresso using Pytorch. In addition, and to the best of our knowledge, …the approach of CNN-LSTM with attention-based has not been used in the task of Arabic Automatic speech recognition (ASR). To fill this gap, this paper proposes a new approach based on CNN-LSTM with attention based method for Arabic ASR. The language model in this approach is trained using RNN-LM and LSTM-LM and based on nondiacritized transcription of the speech corpus. The Standard Arabic Single Speaker Corpus (SASSC), after omitting the diacritics, is used to train and test the deep learning model. Experimental results show that the removal of diacritics decreased out-of-vocabulary and perplexity of the language model. In addition, the word error rate (WER) is significantly improved when compared to diacritized data. The achieved average reduction in WER is 13.52%. Show more

Keywords: Arabic speech recognition, Arabic diacritics, End-to-End deep learning, CNN-LSTM

DOI: 10.3233/JIFS-202841

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6207-6219, 2021

Authors: Wei, Yanxia | Wang, Qinghai

Article Type: Research Article

Abstract: Compared to hesitant fuzzy sets and intuitionistic fuzzy sets, dual hesitant fuzzy sets can model problems in the real world more comprehensively. Dual hesitant fuzzy sets explicitly show a set of membership degrees and a set of non-membership degrees, which also imply a set of important data: hesitant degrees.The traditional definition of distance between dual hesitant fuzzy sets only considers membership degree and non-membership degree, but hesitant degree should also be taken into account. To this end, using these three important data sets (membership degree, non-membership degree and hesitant degree), we first propose a variety of new distance measurements (the …generalized normalized distance, generalized normalized Hausdorff distance and generalized normalized hybrid distance) for dual hesitant fuzzy sets in this paper, based on which the corresponding similarity measurements can be obtained. In these distance definitions, membership degree, non-membership-degree and hesitant degree are of equal importance. Second, we propose a clustering algorithm by using these distances in dual hesitant fuzzy information system. Finally, a numerical example is used to illustrate the performance and effectiveness of the clustering algorithm. Accordingly, the results of clustering in dual hesitant fuzzy information system are compared using the distance measurements mentioned in the paper, which verifies the utility and advantage of our proposed distances. Our work provides a new way to improve the performance of clustering algorithms in dual hesitant fuzzy information systems. Show more

Keywords: Dual hesitant fuzzy set, distance measures, similarity measures, clustering algorithm

DOI: 10.3233/JIFS-202846

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6221-6232, 2021

Authors: Al Tahan, Madeline | Hoskova-Mayerova, Sarka | Davvaz, Bijan

Article Type: Research Article

Abstract: In recent years, fuzzy multisets have become a subject of great interest for researchers and have been widely applied to algebraic structures including groups, rings, and many other algebraic structures. In this paper, we introduce the algebraic structure of fuzzy multisets as fuzzy multi-subnear rings (multi-ideals) of near rings. In this regard, we define different operations on fuzzy multi-ideals of near rings and we generalize some results known for fuzzy ideals of near rings to fuzzy multi-ideals of near rings.

Keywords: Near ring, multiset, fuzzy multiset, fuzzy multi-ideal, fuzzy multi-subnear ring

DOI: 10.3233/JIFS-202914

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6233-6243, 2021

Authors: Park, Choonkil | Ashraf, Shahzaib | Rehman, Noor | Abdullah, Saleem | Aslam, Muhammad

Article Type: Research Article

Abstract: As a generalization of Pythagorean fuzzy sets and picture fuzzy sets, spherical fuzzy sets provide decision makers more flexible space in expressing their opinions. Preference relations have received widespread acceptance as an efficient tool in representing decision makers’ preference over alternatives in the decision-making process. In this paper, some new preference relations are investigated based on the spherical fuzzy sets. Firstly, the deficiency of the existing operating laws is elaborated in detail and three cases are described to identify the accuracy of the proposed operating laws in the context of t-spherical fuzzy environment. Also, a novel score function is proposed …to obtain the consistent value in ranking of the alternatives. The backbone of this research, t-spherical fuzzy preference relation, consistent t-spherical fuzzy preference relations, incomplete t-spherical fuzzy preference relations, consistent incomplete t-spherical fuzzy preference relations, and acceptable incomplete t-spherical fuzzy preference relations are established. Additionally, some ranking and selection algorithms are established using the proposed novel score function and preference relations to tackle the uncertainty in real-life decision-making problems. Finally, evaluation of the product quality of the online shopping platform problem is demonstrated to show the applicability and reliability of proposed technique. Show more

Keywords: Spherical fuzzy Sets, t-spherical fuzzy set, Improved operational laws, Improved score function, preference relations, incomplete preference relations.

DOI: 10.3233/JIFS-202930

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6245-6262, 2021

Authors: Dong, Shi | Zhou, Wengang

Article Type: Research Article

Abstract: Influential node identification plays an important role in optimizing network structure. Many measures and identification methods are proposed for this purpose. However, the current network system is more complex, the existing methods are difficult to deal with these networks. In this paper, several basic measures are introduced and discussed and we propose an improved influential nodes identification method that adopts the hybrid mechanism of information entropy and weighted degree of edge to improve the accuracy of identification (Hm-shell). Our proposed method is evaluated by comparing with nine algorithms in nine datasets. Theoretical analysis and experimental results on real datasets show …that our method outperforms other methods on performance. Show more

Keywords: Influential nodes, complex networks, K-shell, page rank

DOI: 10.3233/JIFS-202943

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6263-6271, 2021

Authors: Sheng, JinFang | Zuo, Huaiyu | Wang, Bin | Li, Qiong

Article Type: Research Article

Abstract:  In a complex network system, the structure of the network is an extremely important element for the analysis of the system, and the study of community detection algorithms is key to exploring the structure of the complex network. Traditional community detection algorithms would represent the network using an adjacency matrix based on observations, which may contain redundant information or noise that interferes with the detection results. In this paper, we propose a community detection algorithm based on density clustering. In order to improve the performance of density clustering, we consider an algorithmic framework for learning the continuous representation of network …nodes in a low-dimensional space. The network structure is effectively preserved through network embedding, and density clustering is applied in the embedded low-dimensional space to compute the similarity of nodes in the network, which in turn reveals the implied structure in a given network. Experiments show that the algorithm has superior performance compared to other advanced community detection algorithms for real-world networks in multiple domains as well as synthetic networks, especially when the network data chaos is high. Show more

Keywords: Complex network, community detection, network embedding, density clustering

DOI: 10.3233/JIFS-202961

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6273-6284, 2021

Authors: Du, Yuqin | Ren, Weijia | Du, Yuhong | Hou, Fujun

Article Type: Research Article

Abstract: A Hamacher operator in a q-rung orthopair trapezoidal fuzzy linguistic environment is studied based on the definition of the q-rung orthopair fuzzy set and the Hamacher aggregation operator. First, we define a new fuzzy variable called q-rung orthopair trapezoidal fuzzy linguistic sets, and the operational laws, score function, accuracy function, comparison rules, and distance measures of the IVPFLVS are defined. Second, based on the Hamacher operator and the q-rung orthopair trapezoidal fuzzy linguistic sets, we propose several q-rung trapezoidal fuzzy linguistic Hamacher operator information aggregation operators, such as the generalized q-rung orthopair trapezoidal fuzzy linguistic Hamacher weighted averaging (q-GROTrFLHWA) operator, …and the generalized q-rung orthopair trapezoidal fuzzy linguistic Hamacher weighted geometric (q-GROTrFLHWG) operator. Third, some desirable properties of the correlation operators, such as idempotency, boundedness, and monotonicity are discussed. Finally, there are two group decision schemes based on q-rung orthopair trapezoidal fuzzy information with known attribute weights. The decision-making scheme is applied to the evaluation of school teaching quality, and the practicability and effectiveness of the scheme are demonstrated by different methods. Show more

Keywords: The q-rung trapezoidal fuzzy linguistic set, multi-attribute decision making, Hamacher operator, application

DOI: 10.3233/JIFS-210056

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6285-6302, 2021

Authors: Xing, Shixiong | Chen, Guohua | Yu, Guoming | Chen, Xiaolan | Sun, Chuan

Article Type: Research Article

Abstract: According to the characteristics of NC milling, an approach for optimization of milling parameters considering high efficiency and low carbon based on gravity search algorithm is proposed. Taking the carbon emission and processing time as the objectives, the cutting rate, feed per tooth, and cutting width as the optimization variables. A multi-objective optimization model of NC milling parameters is established. An non-dominated sorting gravity search algorithm (NSGSA) is used to solve the multi-objective model, and the position update backoff operation is introduced. Finally, taking NC machining process as an example, the multi-objective optimization results and the single objective optimization results …are compared respectively, the actual data show that when the optimization objective is high efficiency and low carbon, the processing time and carbon emissions are 173 and 192 respectively. The comparison results show that the combination of processing parameters obtained by multi-objective optimization is the best, the optimal parameter combination obtained by NSGSA algorithm is verified by grey correlation analysis, and the grey correlation degree of the optimal solution set is 0.81, which is the largest in all solution sets. This approach can help the decision-makers flexibly select the corresponding milling parameters, and provide decision-makers with flexible selection decisions suitable for various scenarios. Show more

Keywords: NC milling, multi-objective model, milling parameter optimization, NSGSA, Grey relational analysis

DOI: 10.3233/JIFS-210059

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6303-6321, 2021

Authors: Guan, Li | Zhang, Jinping | Zhou, Jieming

Article Type: Research Article

Abstract: This work proposes the concept of uncorrelation for fuzzy random variables, which is weaker than independence. For the sequence of uncorrelated fuzzy random variables, weak and strong laws of large numbers are studied under the uniform Hausdorff metric d H ∞ . The results generalize the law of large numbers for independent fuzzy random variables.

Keywords: Fuzzy random variable, uncorrelated, law of large numbers

DOI: 10.3233/JIFS-210099

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6323-6330, 2021