Int. J. Intell. Comput. Cybern.最新文献

{"title":"Multi-attribute group decision-making method with linguistic q-rung orthopair fuzzy information based on bi-direction Choquet integral","authors":"Ling Weng, Jian Lin, Shujie Lv","doi":"10.1108/ijicc-07-2022-0188","DOIUrl":"https://doi.org/10.1108/ijicc-07-2022-0188","url":null,"abstract":"PurposeThe purpose of this paper is to develop the linguistic q-rung orthopair fuzzy set (LqROFS) information VIKOR method based on the bi-direction Choquet integral (BDCI), taking into account the correlation between information. The method can enrich the existing studies related to LqROFS information and better solve the problem of MAGDM problem.Design/methodology/approachSince applying Choquet integral (CI) depict information interaction is a common operation in MAGDM. However, the traditional CI has some limitations. The unidirectional alignment may affect the MAGDM results. Therefore, a LqROFS-VIKOR method based on BDCI is proposed, where BDCI is used to aggregate the decision matrix. Furthermore, it is not reasonable to apply exact numbers to express the similarity between two qualitative data. Then a new method of defining similarity using linguistics is proposed. The similarity is used to calculate attribute weights.FindingsThe validity and potential application of MAGMD method with linguistic q-rung orthopair fuzzy information based on BDCI are demonstrated in a numerical examples study.Originality/valueAccording to the study of available literature, the current research on LqROFS is incomplete. The existing studies of both similarity and aggregate operators have certain shortcomings. The definition of similarity proposed in this paper is more in line with reality. And compared with the existing methods, the BDCI-based aggregate operator can describe the interaction between information more reasonably. Based on this VIKOR method based on BDCI under the LqROFS environment can better select the alternative.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132791859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A survey on blockchain consensus mechanism: research overview, current advances and future directions","authors":"Mingyue Xie, Jun Liu, Shuyu Chen, Mingwei Lin","doi":"10.1108/ijicc-05-2022-0126","DOIUrl":"https://doi.org/10.1108/ijicc-05-2022-0126","url":null,"abstract":"PurposeAs the core technology of blockchain, various consensus mechanisms have emerged to satisfy the demands of different application scenarios. Since determining the security, scalability and other related performance of the blockchain, how to reach consensus efficiently of consensus mechanism is a critical issue in the blockchain.Design/methodology/approachThe paper opted for a research overview on the blockchain consensus mechanism, including the consensus mechanisms' consensus progress, classification and comparison, which are complemented by documentary analysis.FindingsThis survey analyzes solutions for the improvement of consensus mechanisms in blockchain that have been proposed during the last few years and suggests future research directions around consensus mechanisms. First, the authors outline the consensus processes, the advantages and disadvantages of the mainstream consensus mechanisms. Additionally, the consensus mechanisms are subdivided into four types according to their characteristics. Then, the consensus mechanisms are compared and analyzed based on four evaluation criteria. Finally, the authors summarize the representative progress of consensus mechanisms and provide some suggestions on the design of consensus mechanisms to make further advances in this field.Originality/valueThis paper summarizes the future research development of the consensus mechanisms.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130678514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on pedestrian detection based on multi-level fine-grained YOLOX algorithm","authors":"Hong Wang, Yonggui Xie, Shasha Tian, Lu Zheng, Xiaojie Dong, Yueli Zhu","doi":"10.1108/ijicc-05-2022-0161","DOIUrl":"https://doi.org/10.1108/ijicc-05-2022-0161","url":null,"abstract":"PurposeThe purpose of the study is to address the problems of low accuracy and missed detection of occluded pedestrians and small target pedestrians when using the YOLOX general object detection algorithm for pedestrian detection. This study proposes a multi-level fine-grained YOLOX pedestrian detection algorithm.Design/methodology/approachFirst, to address the problem of the original YOLOX algorithm in obtaining a single perceptual field for the feature map before feature fusion, this study improves the PAFPN structure by adding the ResCoT module to increase the diversity of the perceptual field of the feature map and divides the pedestrian multi-scale features into finer granularity. Second, for the CSPLayer of the PAFPN, a weight gain-based normalization-based attention module (NAM) is proposed to make the model pay more attention to the context information when extracting pedestrian features and highlight the salient features of pedestrians. Finally, the authors experimentally determined the optimal values for the confidence loss function.FindingsThe experimental results show that, compared with the original YOLOX algorithm, the AP of the improved algorithm increased by 2.90%, the Recall increased by 3.57%, and F1 increased by 2% on the pedestrian dataset.Research limitations/implicationsThe multi-level fine-grained YOLOX pedestrian detection algorithm can effectively improve the detection of occluded pedestrians and small target pedestrians.Originality/valueThe authors introduce a multi-level fine-grained ResCoT module and a weight gain-based NAM attention module.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132132227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of LSTM model optimized by individual-ordering-based adaptive genetic algorithm in stock forecasting","authors":"Yong He, Xiaohua Zeng, Huan Li, Wenhong Wei","doi":"10.1108/ijicc-04-2022-0104","DOIUrl":"https://doi.org/10.1108/ijicc-04-2022-0104","url":null,"abstract":"PurposeTo improve the accuracy of stock price trend prediction in the field of quantitative financial trading, this paper takes the prediction accuracy as the goal and avoid the enormous number of network structures and hyperparameter adjustments of long-short-term memory (LSTM).Design/methodology/approachIn this paper, an adaptive genetic algorithm based on individual ordering is used to optimize the network structure and hyperparameters of the LSTM neural network automatically.FindingsThe simulation results show that the accuracy of the rise and fall of the stock outperform than the model with LSTM only as well as other machine learning models. Furthermore, the efficiency of parameter adjustment is greatly higher than other hyperparameter optimization methods.Originality/value(1) The AGA-LSTM algorithm is used to input various hyperparameter combinations into genetic algorithm to find the best hyperparameter combination. Compared with other models, it has higher accuracy in predicting the up and down trend of stock prices in the next day. (2) Adopting real coding, elitist preservation and self-adaptive adjustment of crossover and mutation probability based on individual ordering in the part of genetic algorithm, the algorithm is computationally efficient and the results are more likely to converge to the global optimum.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115900215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective particle swarm optimization algorithm using Cauchy mutation and improved crowding distance","authors":"Qingxia Li, Xiaohua Zeng, Wenhong Wei","doi":"10.1108/ijicc-04-2022-0118","DOIUrl":"https://doi.org/10.1108/ijicc-04-2022-0118","url":null,"abstract":"PurposeMulti-objective is a complex problem that appears in real life while these objectives are conflicting. The swarm intelligence algorithm is often used to solve such multi-objective problems. Due to its strong search ability and convergence ability, particle swarm optimization algorithm is proposed, and the multi-objective particle swarm optimization algorithm is used to solve multi-objective optimization problems. However, the particles of particle swarm optimization algorithm are easy to fall into local optimization because of their fast convergence. Uneven distribution and poor diversity are the two key drawbacks of the Pareto front of multi-objective particle swarm optimization algorithm. Therefore, this paper aims to propose an improved multi-objective particle swarm optimization algorithm using adaptive Cauchy mutation and improved crowding distance.Design/methodology/approachIn this paper, the proposed algorithm uses adaptive Cauchy mutation and improved crowding distance to perturb the particles in the population in a dynamic way in order to help the particles trapped in the local optimization jump out of it which improves the convergence performance consequently.FindingsIn order to solve the problems of uneven distribution and poor diversity in the Pareto front of multi-objective particle swarm optimization algorithm, this paper uses adaptive Cauchy mutation and improved crowding distance to help the particles trapped in the local optimization jump out of the local optimization. Experimental results show that the proposed algorithm has obvious advantages in convergence performance for nine benchmark functions compared with other multi-objective optimization algorithms.Originality/valueIn order to help the particles trapped in the local optimization jump out of the local optimization which improves the convergence performance consequently, this paper proposes an improved multi-objective particle swarm optimization algorithm using adaptive Cauchy mutation and improved crowding distance.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125439666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Solving constrained portfolio optimization model using stochastic fractal search approach","authors":"Md. Shahid, Zubair Ashraf, Mohd Shamim, Mohd Shamim Ansari","doi":"10.1108/ijicc-03-2022-0086","DOIUrl":"https://doi.org/10.1108/ijicc-03-2022-0086","url":null,"abstract":"PurposeOptimum utilization of investments has always been considered one of the most crucial aspects of capital markets. Investment into various securities is the subject of portfolio optimization intent to maximize return at minimum risk. In this series, a population-based evolutionary approach, stochastic fractal search (SFS), is derived from the natural growth phenomenon. This study aims to develop portfolio selection model using SFS approach to construct an efficient portfolio by optimizing the Sharpe ratio with risk budgeting constraints.Design/methodology/approachThis paper proposes a constrained portfolio optimization model using the SFS approach with risk-budgeting constraints. SFS is an evolutionary method inspired by the natural growth process which has been modeled using the fractal theory. Experimental analysis has been conducted to determine the effectiveness of the proposed model by making comparisons with state-of-the-art from domain such as genetic algorithm, particle swarm optimization, simulated annealing and differential evolution. The real datasets of the Indian stock exchanges and datasets of global stock exchanges such as Nikkei 225, DAX 100, FTSE 100, Hang Seng31 and S&P 100 have been taken in the study.FindingsThe study confirms the better performance of the SFS model among its peers. Also, statistical analysis has been done using SPSS 20 to confirm the hypothesis developed in the experimental analysis.Originality/valueIn the recent past, researchers have already proposed a significant number of models to solve portfolio selection problems using the meta-heuristic approach. However, this is the first attempt to apply the SFS optimization approach to the problem.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116799097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Type-2 fuzzy logic applications designed for active parameter adaptation in metaheuristic algorithm for fuzzy fault-tolerant controller","authors":"H. Patel, V. Shah","doi":"10.1108/ijicc-01-2022-0011","DOIUrl":"https://doi.org/10.1108/ijicc-01-2022-0011","url":null,"abstract":"PurposeIn recent times, fuzzy logic is gaining more and more attention, and this is because of the capability of understanding the functioning of the system as per human knowledge-based system. The main contribution of the work is dynamically adapting the important parameters throughout the execution of the flower pollination algorithm (FPA) using concepts of fuzzy logic. By adapting the main parameters of the metaheuristics, the performance and accuracy of the metaheuristic have been improving in a varied range of applications.Design/methodology/approachThe fuzzy logic-based parameter adaptation in the FPA is proposed. In addition, type-2 fuzzy logic is used to design fuzzy inference system for dynamic parameter adaptation in metaheuristics, which can help in eliminating uncertainty and hence offers an attractive improvement in dynamic parameter adaption in metaheuristic method, and, in reality, the effectiveness of the interval type-2 fuzzy inference system (IT2 FIS) has shown to provide improved results as matched to type-1 fuzzy inference system (T1 FIS) in some latest work.FindingsOne case study is considered for testing the proposed approach in a fault tolerant control problem without faults and with partial loss of effectiveness of main actuator fault with abrupt and incipient nature. For comparison between the type-1 fuzzy FPA and interval type-2 fuzzy FPA is presented using statistical analysis which validates the advantages of the interval type-2 fuzzy FPA. The statistical Z-test is presented for comparison of efficiency between two fuzzy variants of the FPA optimization method.Originality/valueThe main contribution of the work is a dynamical adaptation of the important parameters throughout the execution of the flower pollination optimization algorithm using concepts of type-2 fuzzy logic. By adapting the main parameters of the metaheuristics, the performance and accuracy of the metaheuristic have been improving in a varied range of applications.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130624427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Jaya Honey Badger optimization-based deep neuro-fuzzy network structure for detection of (SARS-CoV) Covid-19 disease by using respiratory sound signals","authors":"J. Dar, K. Srivastava, Sajaad Ahmad Lone","doi":"10.1108/ijicc-03-2022-0062","DOIUrl":"https://doi.org/10.1108/ijicc-03-2022-0062","url":null,"abstract":"PurposeThe Covid-19 prediction process is more indispensable to handle the spread and death occurred rate because of Covid-19. However early and precise prediction of Covid-19 is more difficult because of different sizes and resolutions of input image. Thus these challenges and problems experienced by traditional Covid-19 detection methods are considered as major motivation to develop JHBO-based DNFN.Design/methodology/approachThe major contribution of this research is to design an effectual Covid-19 detection model using devised JHBO-based DNFN. Here, the audio signal is considered as input for detecting Covid-19. The Gaussian filter is applied to input signal for removing the noises and then feature extraction is performed. The substantial features, like spectral roll-off, spectral bandwidth, Mel-frequency cepstral coefficients (MFCC), spectral flatness, zero crossing rate, spectral centroid, mean square energy and spectral contract are extracted for further processing. Finally, DNFN is applied for detecting Covid-19 and the deep leaning model is trained by designed JHBO algorithm. Accordingly, the developed JHBO method is newly designed by incorporating Honey Badger optimization Algorithm (HBA) and Jaya algorithm.FindingsThe performance of proposed hybrid optimization-based deep learning algorithm is estimated by means of two performance metrics, namely testing accuracy, sensitivity and specificity of 0.9176, 0.9218 and 0.9219.Research limitations/implicationsThe JHBO-based DNFN approach is developed for Covid-19 detection. The developed approach can be extended by including other hybrid optimization algorithms as well as other features can be extracted for further improving the detection performance.Practical implicationsThe proposed Covid-19 detection method is useful in various applications, like medical and so on.Originality/valueDeveloped JHBO-enabled DNFN for Covid-19 detection: An effective Covid-19 detection technique is introduced based on hybrid optimization–driven deep learning model. The DNFN is used for detecting Covid-19, which classifies the feature vector as Covid-19 or non-Covid-19. Moreover, the DNFN is trained by devised JHBO approach, which is introduced by combining HBA and Jaya algorithm.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125470801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Solving vehicle routing problem with time windows using metaheuristic approaches","authors":"Zeynep Aydınalp, Dogan Özgen","doi":"10.1108/ijicc-01-2022-0021","DOIUrl":"https://doi.org/10.1108/ijicc-01-2022-0021","url":null,"abstract":"PurposeDrugs are strategic products with essential functions in human health. An optimum design of the pharmaceutical supply chain is critical to avoid economic damage and adverse effects on human health. The vehicle-routing problem, focused on finding the lowest-cost routes with available vehicles and constraints, such as time constraints and road length, is an important aspect of this. In this paper, the vehicle routing problem (VRP) for a pharmaceutical company in Turkey is discussed.Design/methodology/approachA mixed-integer programming (MIP) model based on the vehicle routing problem with time windows (VRPTW) is presented, aiming to minimize the total route cost with certain constraints. As the model provides an optimum solution for small problem sizes with the GUROBI® solver, for large problem sizes, metaheuristic methods that simulate annealing and adaptive large neighborhood search algorithms are proposed. A real dataset was used to analyze the effectiveness of the metaheuristic algorithms. The proposed simulated annealing (SA) and adaptive large neighborhood search (ALNS) were evaluated and compared against GUROBI® and each other through a set of real problem instances.FindingsThe model is solved optimally for a small-sized dataset with exact algorithms; for solving a larger dataset, however, metaheuristic algorithms require significantly lesser time. For the problem addressed in this study, while the metaheuristic algorithms obtained the optimum solution in less than one minute, the solution in the GUROBI® solver was limited to one hour and three hours, and no solution could be obtained in this time interval.Originality/valueThe VRPTW problem presented in this paper is a real-life problem. The vehicle fleet owned by the factory cannot be transported between certain suppliers, which complicates the solution of the problem.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114946336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on electronic word-of-mouth for product and service quality improvement: bibliometric analysis and future directions","authors":"Yajun Wang, Xinyu Meng, Chang Xu, Meng Zhao","doi":"10.1108/ijicc-03-2022-0065","DOIUrl":"https://doi.org/10.1108/ijicc-03-2022-0065","url":null,"abstract":"PurposeThis paper aims to analyze high-quality papers on the research of electronic word-of-mouth (eWOM) for product and service quality improvement from 2009 to 2022, in order to fully understand their historical progress, current situation and future development trend.Design/Methodology/ApproachThis paper adopts the bibliometrics method to analyze the relevant literature, including publishing trend and citation status, regional and discipline area distribution, and influential publications. Secondly, the VOSviewer is used for literature co-citation analysis and keyword co-occurrence analysis to obtain the basic literature and research hotspots in this research field.FindingsFirstly, the study finds that the number of publications basically shows an increasing trend, and those publications are mainly published in tourism journals. In addition, among these papers, China has the largest number of publications, followed by the USA and South Korea. Through co-citation analysis of literature and keyword co-occurrence analysis, 22 foundational papers and six main research topics are obtained in this paper. Finally, this paper elaborates on the development trend of the research topic and future research directions in detail.Originality/valueThis is the first paper that uses bibliometrics to analyze and review relevant researches on eWOM for product and service quality improvement, which is helpful for researchers to quickly understand its development status and trend. This review also provides some future research directions and provides a reference for further research.","PeriodicalId":352072,"journal":{"name":"Int. J. Intell. Comput. Cybern.","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131568016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}