Journal of Intelligent & Fuzzy Systems - Volume 43, issue 3

Authors: Azimirad, Ehsan

Article Type: Research Article

Abstract: Edge Detection is the first stage in the image division into separate parts. Image division is the partitioning of a digital image to the different zones or the set of pixels. Edge detection is one of the techniques applied in digital image processing often. The purpose of detecting pixels is to match the edges in the image. Filtering, Enhancement, and Detection are three steps in edge detection. Images are usually destroyed by casual changes in intensity intervals called noise or confusion. some noise variations include salt and pepper, pulse, and Gaussian. However, there is a relation between edge detection power …and noise reduction. Using filters to the noise reduction causes the loss of edge detection power. For facilitating the edges detection, it is essential for the determination of pixels’ intensity constraints in their neighborhood. Many points in an image have a nontransparent slope, and all of them are not the edges of the joint space. Therefore, some of the linear and nonlinear methods such as Sobel, Prewitt, and Robert have to be used to determine the edge points. The fuzzy logic and the system based on it, is one of the most effective methods for edge detection. This paper presents an optimized rule-based fuzzy inference system and designs the efficiency mask matric. The simulation results for edge detection are presented using the traditional edge detection techniques, including Binary Filter, Sobel Filter, Prewitt Filter, and Robert Filter. Also, it is presented using the fuzzy approach. The simulation results show that the designed fuzzy system has been able to detect the edges of the image more accurately and help to increase the sharpness and quality of the edges. Therefore, the proposed method has more accurate and more reliable results and reduces false edge detection comparison to the traditional methods. Show more

Keywords: Edge detection, fuzzy sets, optimized fuzzy system, membership functions

DOI: 10.3233/JIFS-213008

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2363-2373, 2022

Authors: Mystica, A. | Senthil kumar, V.S. | Sakthi abirami, B.

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-213032

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2375-2390, 2022

Authors: Bokir, Abdullah | Narasimha, V.B

Article Type: Research Article

Abstract: High utility mining is gaining prominence, and with the increasing set of business intelligence models, the scope of such significant practices is high. Rather than focusing only on profitability as one key utility metric, today’s organizations believe in having more robust levels of the multi-objective filtering process. In this manuscript, a contemporary model of the high utility mining process is proposed, wherein the multiple averages are used for grading the recommendation of the itemsets for merchandise. The model’s key advantage is its dynamic approach. The goods-related period of the average time interval can be flexible, alongside the fusion of multiple …utility thresholds of diversified features chosen for itemsets recommendation. The performance analysis has been carried out by using a multi-fold cross-validation strategy. The results obtained for cross-validation show that the proposed model is outperforming the contemporary models with significant precision, specificity, sensitivity, and accuracy having values 97%, 95%, 98%, and 97% in respective order. Whereas, the contemporary models HUPM-MUO and MOEA-FHUI have obtained 93% and 90%, 88% and 82%, 89%, and 84%, and 89% and 83% in respective order of the corresponding metrics. The experimental study of the model denotes the effectiveness and ease with which the solution can generate results and produce significant output in the real-time environment for more dynamic and periodic decisions by different organizations. Show more

Keywords: High Utility Mining, multiple-utility factors, economic order quantity, exponential moving average, inventory storage cost

DOI: 10.3233/JIFS-213037

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2391-2405, 2022

Authors: Jiang, Huimin | Guo, Gaicong | Sabetzadeh, Farzad | Chan, Kit Yan

Article Type: Research Article

Abstract: Previous studies developed consumer preference models mainly through customer surveys, ignoring the variability of consumer preferences over time. In addition, it is difficult to obtain time series data based on the customer surveys. In recent years, some previous studies tried to analyse consumer preferences based on online reviews. However, they have not solved the problems of modelling variational consumer preference based on time series data with the consideration of the ambiguity of emotions expressed by customers in online reviews. To solve the above problems, this article proposes the particle swarm optimization (PSO) based dynamic evolving neural-fuzzy inference system (DENFIS) method …to model variational consumer preferences based on online customer reviews. Using the time series data mined by the sentiment analysis method and the product attribute settings of the review products, the PSO-based DENFIS method is offered to dynamically model consumer preferences, in which PSO is used to adjust DENFIS parameters adaptively. Show more

Keywords: Consumer preference, opinion mining, DENFIS, particle swarm optimization, new product development

DOI: 10.3233/JIFS-213057

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2407-2418, 2022

Authors: Chotikunnan, Phichitphon | Panomruttanarug, Benjamas

Article Type: Research Article

Abstract:  Iterative Learning Control (ILC) is an intelligent control algorithm that can effectively handle a tracking error in any system that operates in a repetitive manner. In practice, it is hardly possible to implement a single gain learning control law to improve the tracking performance due to the existence of large transient growth. To prevent the growth, this paper proposes a time-varying learning control design using the unique concept of fuzzy logic control to track the desired trajectory as well as the desired control input signal. The proposed control design is developed on both serial and parallel ILC configurations. The two …configurations are initially constructed and implemented on a robotic manipulator with the use of a single gain learning control law. To avoid bad transients, the gain adjustment mechanism based on fuzzy logic control is introduced to vary the learning gain in each time step for enhancing the robustness of the system. According to the simulation and experiment on a robotic manipulator, both ILC structures with the proposed mechanism achieve the desired learning performance without bad transients. Show more

Keywords: Iterative learning control, serial ILC, parallel ILC, fuzzy logic control, robotic manipulator

DOI: 10.3233/JIFS-213082

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2419-2434, 2022

Authors: Han, Meng | Shan, Zhihui | Han, Qiang

Article Type: Research Article

Abstract: High utility quantitative itemsets (HUQI) mining is a new research topic in the field of data mining. It not only provides high utility itemset (HUI), but also provides quantitative information of individual item in the itemset. HUQI can provide decision makers with information about items and their purchase quantities. However, the currently proposed HUQI mining algorithms assume that the datasets are static. In order to solve this problem, an incremental quantitative utility list (IQUL) data structure is proposed to store item information, including item name, item number, transaction weight utility of item, each entry in the list stores the transaction …identifier, the utility of the original data, the remaining utility, the utility of the incremental data, the remaining utility, and the sum of the utility and the remaining utility. When data is inserted, the item information will be updated. Based on IQUL, an incrementally updating HUQI (IHUQI) mining algorithm is proposed to mine HUQI on incremental update data. A large number of experiments on real datasets show that the IHUQI algorithm can effectively mine HUQI Experimental results show better performance on sparse datasets. Show more

Keywords: Incremental mining, high utility quantitative itemsets, high utility itemsets, utility list, itemsets mining

DOI: 10.3233/JIFS-213136

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2435-2448, 2022

Authors: Ge, Liang | Lin, Yongquan | Li, Senwen | Zeng, Bo

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-213317

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2449-2462, 2022

Authors: Chai, Shaolong | Wang, Zeng

Article Type: Research Article

Abstract: In view of the shortcomings of the existing evaluation methods in fully considering the fuzziness and randomness of product design evaluation, a novel product design evaluation method based on FAHP and cloud model is proposed. First, a hierarchical structure model of product design evaluation is established. Second, fuzzy pairwise comparison of criteria is constructed through questionnaire survey, and the digital characteristics of weight cloud model are acquired by the proposed fuzzy weight model. Then, based on the factor scores, the digital characteristics of scoring cloud model are obtained by backward cloud. Finally, the digital characteristics of comprehensive evaluation cloud model …are obtained by using the proposed improved fuzzy composite operator, and the forward cloud is used to get the cloud picture for evaluation. Taking reading lamp as an example, the feasibility and effectiveness of the proposed method are verified. The results show that compared with the other two methods, the Kendall rank correlation coefficients of entropy of the method are increased by 0.17 and 0.33, respectively, which proves that the method achieves more accurate evaluation result under the complex criteria, and provides a more effective tool for decision makers and designers to evaluate and optimize design schemes. Show more

Keywords: FAHP, cloud model, design evaluation, reading lamp

DOI: 10.3233/JIFS-213331

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2463-2483, 2022

Authors: Cebi, Selcuk | Gündoğdu, Fatma Kutlu | Kahraman, Cengiz

Article Type: Research Article

Abstract: Risk assessment takes place depending on the expertise and subjective linguistic assessments of experts. Expert judgements are collected via a questionnaire or an interview including qualitative data. Pessimistic or optimistic status of experts can affect their perceptions on risk. Furthermore, expert judgments are affected by questions’ structure based on whether it is a positive type question (e.g., ‘What is the occurrence probability of the accident?) or a negative type question (e.g., ‘What is the non-occurrence probability of the accident?). All of these cases create uncertainties in the risk assessment process. For this reason, there are various studies using fuzzy risk …analysis models to address these uncertainties in risk assessment. However, there is not any risk assessment tool that considers the uncertainties caused by the factors mentioned above, simultaneously. Therefore, in this paper, we introduce the concept of decomposed fuzzy sets (DFS) to model human thoughts and perceptions in a more realistic and detailed way through optimistic and pessimistic membership functions. We present the basic operations on decomposed fuzzy sets and their properties. To demonstrate the utility of the proposed method, the method is applied to operational risk analysis in business processes. The data used in the application are collected from the managerial board of a construction company. The application results and advantages of the proposed method are presented together with a comparative analysis. Show more

Keywords: Intuitionistic fuzzy sets, fuzzy set theory, decomposed fuzzy sets, risk assessment, business management

DOI: 10.3233/JIFS-213385

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2485-2502, 2022

Authors: Thillai Rani, M. | Sai Pradeep, K.P. | Sivakumar, R. | Suresh Kumar, S.

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-213406

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2503-2514, 2022