Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Purchase individual online access for 1 year to this journal.
Price: EUR 315.00Impact Factor 2023: 2
The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Batista Contarato, Rodrigo | Pereira, Rogério Passos do Amaral | Valadão, Carlos Torturella | Cuadros, Marco A.S.L. | Salles, José Leandro Felix | Almeida, Gustavo Maia de
Article Type: Research Article
Abstract: The generalized predictive controller (GPC) is an efficient strategy for controlling processes with time-varying parameters, as long as the GPC tuning parameters are chosen correctly. This study aims to present a new online tuning algorithm for the parameters of the GPC. The controllers are initially tuned by a model simulation (offline), via genetic algorithm, seeking quick answers and a small error. After variations in the setpoint, injection of disturbances in the output of the plant, and variations in the gains of the system operating in closed loop, the algorithm performs an online adjustment of these parameters using Fuzzy Logic. Based …on the error information between the setpoint and the controlled variable and the variation of this error, the algorithm readjusts the tuning parameters of the GPC, so the performance of the control system response is not degraded. The algorithm is validated via model simulations representing the main characteristics of industrial plants. In the simulations, tests are presented by applying disturbances in the output of the plant, changing the dynamics of the model, and changing the setpoint. It is shown that the performance indexes of each plant are presented as being at least similar to those presented in [1 ], because it is still widely used in recent applications, and in some cases of variation of the dynamics of the plant, the proposed algorithm remained with a satisfactory result, while the presented by [1 ] became unstable. Show more
Keywords: Predictive control, fuzzy logic, tuning algorithm, process control
DOI: 10.3233/JIFS-212322
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5501-5513, 2022
Authors: Qu, Shaojian | Jiang, Shan | Feng, Can
Article Type: Research Article
Abstract: The principle of maximum utility is generally adopted to design the optimal insurance contracts, which should consider the influence of different factors such as the probability of accident, premium, compensation, and so on. However, most literatures deal with these variables from a static perspective. This paper considers the accident probability and the value of insurance subject based on the time of accident, which is rarely involved in the previous studies and considers the utility function of the insurer and the policyholder from a dynamic perspective. Firstly, to make this model more universally applicable, we establish an insurance model that considers …the time of the accident and different premium payment forms for policy-holders and insurers respectively. Next, we derive a robust premium insurance model based on min-max regret, in which the time of the accident can be assumed to be certain and uncertain respectively. Then, we conduct numerical experiments and analyze the utility of the policy-holders, demonstrating guarantee period and value of insurance subject are significant when insuring and derive the optimal coverage rate. These results also show that the insurance model that takes into account the time of accident performs better. Show more
Keywords: Time of accident, premium payment, value of insurance subject, min-max regret
DOI: 10.3233/JIFS-212391
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5515-5534, 2022
Authors: Raja, K. | Patan, Muzeeb Khan | Ahmed, Md. Azahar | Ganeshan, P.
Article Type: Research Article
Abstract: Integration of renewable energy sources into existing grid influence the stability of the power system. This article introduces the application of cascade controller in hybrid power system which enhance the frequency stability during power perturbations of the load and generation. For this study, a thermal power unit is considered with integration of a microgrid consist of regular diesel generator, renewable power generating units, energy storage and other power managing devices. Proportional-integral and proportional-integral-derivative (PI-PID) cascade controller is provided for this hybrid power system to reduce the frequency oscillations during system uncertainties. The optimal values of the PI-PID controller are achieved …by using water evaporation optimization (WEO) algorithm with fast convergence rate. Investigations are carried out in different scenarios of the IM and results are compared with the PID controller to showcase the advantages of the cascade controller for frequency regulation. Simulations are carried out in MATLAB-SIMULINK® software environment. Show more
Keywords: Frequency control, microgrid, PI-PID cascade controller, water evaporation algorithm
DOI: 10.3233/JIFS-212434
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5535-5549, 2022
Authors: Peng, Peng | Ni, Zhiwei | Wu, Zhangjun | Zhu, Xuhui | Xia, Pingfan
Article Type: Research Article
Abstract: In order to further improve the enthusiasm of spatial crowdsourcing workers, considering the service quality of workers, different incentive strategies are proposed and tasks are assigned. Firstly, the incentive model is constructed from the unit time revenue of task and online idle time, and the evaluation function of the evaluation model is constructed; Secondly, the task allocation is transformed into a combinatorial optimization problem by delay matching, and an improved glowworm swarm algorithm is proposed to solve the problem by discrete coding, introducing six kinds of mobile modes, adaptive probability matching and infeasible solution processing; Finally, the algorithm is used …to solve the task allocation. The experimental results show that compared with the travel cost minimization strategy and random allocation strategy, the positive incentive index of the proposed strategy is improved by 11.79% and 14.60% respectively, and the fair incentive index is improved by 0.83% and 0.22% respectively, which can effectively improve the positive incentive range and incentive fairness of workers. Show more
Keywords: Spatial crowdsourcing, service quality, task assignment, glowworm swarm algorithm
DOI: 10.3233/JIFS-212531
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5551-5566, 2022
Authors: Çoban, Sezer | Kiracı, Kasım | Akan, Ercan | Uzun, Metin
Article Type: Research Article
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly used in the military field. Especially in recent years, UAVs have been a very effective instrument in gaining airspace superiority and military success. Many countries compete with each other to develop better UAV technology or improve the technical features of UAVs. Therefore, it is critical to determine which UAV has the best performance, considering technical and operational characteristics, because the vehicles with more advanced performance can provide countries with strategic superiority. The purpose of this study is to investigate the technical, cost, and operational performance of Medium Altitude Long Endurance UAVs (MALE UAVs). In …the study, as a result of a wide literature review, we determined a performance criterion for this type of vehicle. The model presented here uses an Interval Type-2 Fuzzy Analytical Hierarch Process (IT2FAHP) and an Interval Type-2 Fuzzy Technique for Order of Preference by Similarity to an Ideal Solution (IT2FTOPSIS) hybrid method. The findings indicate that some MALE UAVs have superior technical and operational performance over others and demonstrate that range, max take-off weight, and payload are important criteria in determining the performance and superiority of these vehicles. Show more
Keywords: MALE UAV selection, AHP, TOPSIS, interval type-2 fuzzy sets
DOI: 10.3233/JIFS-212574
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5567-5594, 2022
Authors: Mishra, Atul | Shaikh, Soharab Hossain | Sanyal, Ratna
Article Type: Research Article
Abstract: In natural language processing, multiword expressions (MWEs) play a significant role in understanding the context and meaning of a sentence. A MWE comprises two or more words that are handled as if they were one. MWE has the property that the constituent words are consistent and are often used in related contexts. Hindi is used as a case study. We employed three properties: linguistic or syntactical pattern, a relationship between constituent words, and context similarity and proposed a three-phase hybrid approach to extract MWE from unstructured Hindi text. Experimental analysis and comparison of results on the TDIL dataset show the …superiority of the proposed hybrid method over the context-based method and association-based methods. Show more
Keywords: Association score, hybrid method, cross-lingual information retrieval, rule extraction
DOI: 10.3233/JIFS-212595
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5595-5605, 2022
Authors: Pavendan, K. | Nagarajan, V.
Article Type: Research Article
Abstract: Biological wastewater treatment with the use of algae-bacteria consortia for the uptake of nutrient and recovery of resource is considered as the ‘paradigm shift’ from the process of mainstream wastewater treatment plants (WWTPs) so as to mitigate the pollution and thus promoting the circular economy. In this regard, the application of machine learning algorithms (MLAs) was found to be effectual and beneficial for the prediction of uncertain performances in the process of treatment and it shows a satisfactory result for the effective optimization, monitoring, uncertainty prediction and so on in the environment systems. The proposed approach aims at modelling the …treatment of wastewater, growth of micro algae and flocculation harvesting at the photobioreactor (PBR) along with the utilization of machine learning techniques. Initially, the raw data from the PBR was taken and is pre-processed using z-score normalization technique followed by extraction and selection of features that are more appropriate. The Adaptive neuro-fuzzy inference system (ANFIS) model is built along with the modified Fuzzy C-Means algorithm (MFCM) so as to cluster the huge amount of data. ANFIS is employed for the estimation of controller output parameters and for controlling the temperature inside the reactor. The output controller parameter performance can be enhanced by the use of optimization approach. The discrete Multilayer perceptron (DMLP) with the hyper tuning parameters of Iterative Levi’s Flight Dependent Cuckoo search optimization algorithm (ILF-CSO) is employed for the prediction purpose of attained cultivation growth rate and the pH of treated wastewater. The optimization technique based on machine learning model in turn offers the best possible solution needed for the estimation of output parameters. Thus, the removal rate of effluent T-N concentrations from the wastewater treatment is predicted with some intervals of day. At last, the performance is estimated in terms of growth rate, temperature variations, biomass, nitrate and phosphate concentrations, and error rates (RMSE, APE), and determination coefficient (R2). The attained outcome shows that the presented model is effectual and has the potential to apply for controlling and predicting the biological wastewater treatment plants. Show more
Keywords: Wastewater treatment, micro algae growth, flocculation harvesting, photo-bioreactor, modified fuzzy C-Means, discrete multilayer perceptron, ILF-CSO, effluent T-N concentrations, biomass production
DOI: 10.3233/JIFS-212676
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5607-5620, 2022
Authors: Bharathi, P. Divya | Narayanan, V. Anantha | Sivakumar, P. Bagavathi
Article Type: Research Article
Abstract: With the rapid industrialization and urbanization worldwide, air quality levels are deteriorating at an unprecedented rate and posing a substantial threat to humans and the environment. This brings the concern to effectively monitor and forecast air quality levels in real-time. Conventional air quality monitoring stations are built based on centralized architectures involving high latency, communication technologies demanding high power, sensors involving high costs and decision making with moderate accuracy. To address the limitations of the existing systems, we propose a smart and distinct Air Quality Monitoring and Forecasting system embracing Fog Computing with IoT and Deep Learning (DL). The system …is a three-layered architecture with the Sensing layer first, Fog Computing layer in between, and Cloud Computing layer at the end. Fog Computing is a powerful new generation paradigm that brings storage, computation, and networking at the edge of the IoT network and reduce network latency. A DL based BiLSTM (Bidirectional Long Short-Term Memory) model is deployed in the Fog Computing layer. The proposed system aims at real-time monitoring and accurate air quality forecasting to support decision making and aid timely prevention and control of pollutant emissions by alerting the stakeholders when a dangerous Air Quality Index (AQI) is expected. Experimental results show that the BiLSTM model has a better predictive performance considering the meteorological parameters than the baseline models in terms of MAE and RMSE. A proof of concept realizing the proposed system is elaborated in the paper. Show more
Keywords: Air quality monitoring, air quality prediction, fog computing, deep learning, bi-directional long short-term memory
DOI: 10.3233/JIFS-212713
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5621-5642, 2022
Authors: Zhang, Yapeng | Guo, Yanling | Xiao, Yaning | Tang, Wenxiu | Zhang, Haoyu | Li, Jian
Article Type: Research Article
Abstract: The material constriction is one of the important factors that influence the forming accuracy of selective laser sintering (SLS). Currently, in order to reduce the shrinkage and improve the quality of products, the optimal combination of machining process parameters is mainly determined by numerous experiments. This often takes valuable time and costs a lot, but the results are mediocre. With the development of intelligent optimization algorithms, they are applied in various disciplines for solving complex problems. Hence, for reducing the shrinkage of parts and overcoming the limitation in the optimization of the process parameters, this paper proposes a novel hybrid …improved Hunger Games Search algorithm (HGS) with extreme learning machine (ELM) model for predicting the shrinkage of parts. Firstly, the orthogonal experiments were conducted based on the five key process parameters, the obtained parts datasets were divided into the training set and test set. Secondly, the Cube mapping and refracted opposition-based learning strategies are adopted to increase the convergence speed and solution accuracy of HGS. In addition, the regression prediction model was constructed with the improved HGS(IHGS) and ELM, and this model is trained using the training set. Finally, the test set is used to evaluate the trained model and find the optimal combination of process parameters with the lowest shrinkage of parts. The experimental results suggest that the IHGS-ELM model proposed in this study has high forecasting precision, with the R2 and RMSE are only 0.9124 and 0.2433, respectively. This model can guide the laser sintering process of polyether sulfone (PES) powder. Show more
Keywords: Selective laser sintering, shrinkage, hunger games search, cube mapping, refracted opposition-based learning
DOI: 10.3233/JIFS-212799
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5643-5659, 2022
Authors: Zhang, Dan | Ma, Yingcang | Zhu, Hengdong | Smarandache, Florentin
Article Type: Research Article
Abstract: The traditional neutrosophic clustering method only performs cluster analysis on the data itself, and often ignores the supervision information of data. In order to solve the above problems, a label-guided weighted semi-supervised neutrosophic clustering algorithm is proposed in the paper. On the one hand, the paired constraint information is used to construct the supervision weight coefficient and the distance measurement learning is combined to re-measure the degree of membership of the data and the cluster center; On the other hand, by minimizing the sum of squares of error between membership matrix and label matrix, the purpose of clustering results guided …by label information is realized. Experiments on various data sets and comparisons with other clustering algorithms show that the new clustering algorithm can make full use of supervisory information and improve the accuracy of clustering. Show more
Keywords: Semi-supervised clustering, label information, neutrosophic set, clustering
DOI: 10.3233/JIFS-212812
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 5661-5672, 2022
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl