Journal of Intelligent & Fuzzy Systems - Volume 42, issue 2

Authors: Malik, Hasmat | Chaudhary, Gopal | Srivastava, Smriti

Article Type: Editorial

Abstract: The digital transformation (DT) is the acquiring the digital tool, techniques, approaches, mechanism etc. for the transformation of the business, applications, services and upgrading the manual process into the automation. The DT enable the efficacy of the system via automation, innovation, creativities. The another concept of DT in the engineering domain is to replace the manual and/or conventional process by means of automation to handle the big-data problems in an efficient way and harness the static/dynamic system information without knowing the system parameters. The DT represents the both opportunities and challenges to the developer and/or user in an organization, such …as development and adaptation of new tool and technique in the system and society with respect to the various applications (i.e., digital twin, cybersecurity, condition monitoring and fault detection & diagnosis (FDD), forecasting and prediction, intelligent data analytics, healthcare monitoring, feature extraction and selection, intelligent manufacturing and production, future city, advanced construction, resilient infrastructure, greater sustainability etc.). Additionally, due to high impact of advanced artificial intelligent, machine learning and data analytics techniques, the harness of the profit of the DT is increased globally. Therefore, the integration of DT into all areas deliver a value to the both users as well as developer. In this editorial fifty-two different applications of DT of distinct engineering domains are presented, which includes its detailed information, state-of-the-art, methodology, proposed approach development, experimental and/or emulation-based performance demonstration and finally conclusive summary of the developed tool/technique along with the future scope. Show more

Keywords: Digital transformation, advancement, artificial intelligence, machine learning, application, data analytics, cybersecurity, condition monitoring, fault detection and diagnosis, prediction, forecasting, renewable energy, feature extraction, feature selection, healthcare, greater sustainability, resilient infrastructure, automation

DOI: 10.3233/JIFS-189787

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 615-622, 2022

Authors: Wang, Caichuan | Li, Jiajun

Article Type: Research Article

Abstract: The decision on the investment project is to analyze the feasibility and rationality of the project plan from multiple angles. However, due to the limitations of the actual project investment decision-making, this paper proposes a group decision making method based multifunctional intuitively fuzzy VIKOR interval sets. Firstly, according to the established investment decision-making model, the first round of preliminary candidate project schemes is selected. According to the definition of interval intuitionistic fuzzy sets and the traditional VIKOR method, established the research method of this article, and the project investment decision-making model based on VIKOR interval intuitionistic fuzzy sets is established. …Finally, the project schemes are sorted according to the closeness degree of schemes. The results show that when sorting each candidate by Qi value, A4 > A3 > A2 > A1 can be obtained. Because Q4 = 0, Q3 = 0.31, the condition q3-q4 > 0.25 is satisfied. It is concluded that the method can not only meet the needs of actual decision-making, but also has strong operability and practicability. The research results have reference value and guiding significance for project investment decision-making, and can promote the sustainable development of the project. Show more

Keywords: Project investment decision, break intuitively vague sets, VIKOR method, multi-attribute group decision making method

DOI: 10.3233/JIFS-189735

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 623-631, 2022

Authors: Malik, Hasmat | Khurshaid, Tahir | Almutairi, Abdulaziz | Alotaibi, Majed A.

Article Type: Research Article

Abstract: In this paper, an intelligent approach for short-term wind speed forecasting (STWSF) is proposed. The STWSF models are developed to forecast the wind speed into a multi-step ahead forecasting, which is used to demonstrate the daily forecast results in One-Step-Ahead (OSA), Two-Step-Ahead (TSA), and Three-Step-Ahead (ThSA) based forecasting manner. To demonstrate the performance and results of the proposed approach, the real-site logged dataset is used for training and testing phase of the year 2015 to 2017. The STWSF is achieved recursively by utilizing the forecasted data in step-1 (OSA) as an input to generate the next forecasting data (in step-2 TSA) …and the process is achieved upto level of step-3 (ThSA) forecasting. In order to results demonstration of fair adoptability of the proposed approach, different neural networks (NNs) models are developed for the same dataset, which shows that the proposed STWSF approach is outperformed and can be utilized for other locations for future applications. Show more

Keywords: Neural networks, short-term-forecasting, forecasting, multi-step-ahead, wind speed

DOI: 10.3233/JIFS-189736

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 633-646, 2022

Authors: Raveendran, Arun Prasath | Alzubi, Jafar A. | Sekaran, Ramesh | Ramachandran, Manikandan

Article Type: Research Article

Abstract: This Ensuing generation of FPGA circuit tolerates the combination of lot of hard and soft cores as well as devoted accelerators on a chip. The Heterogene Multi-Processor System-on-Chip (Ht-MPSoC) architecture accomplishes the requirement of modern applications. A compound System on Chip (SoC) system designed for single FPGA chip, and that considered for the performance/power consumption ratio. In the existing method, a FPGA based Mixed Integer Programming (MIP) model used to define the Ht-MPSoC configuration by taking into consideration the sharing hardware accelerator between the cores. However, here, the sharing method differs from one processor to another based on FPGA architecture. …Hence, high number of hardware resources on a single FPGA chip with low latency and power targeted. For this reason, a fuzzy based MIP and Graph theory based Traffic Estimator (GTE) are proposed system used to define New asymmetric multiprocessor heterogene framework on microprocessor (AHt-MPSoC) architecture. The bandwidths, energy consumption, wait and transmission range are better accomplished in this suggested technique than the standard technique and it is also implemented with a multi-task framework. The new Fuzzy control-based AHt-MPSoC analysis proves significant improvement of 14.7 percent in available bandwidth and 89.8 percent of energy minimized to various traffic scenarios as compared to conventional method. Show more

Keywords: FPGA, MPSoC, hardware accelerators, MIP model, fuzzy control, GTE

DOI: 10.3233/JIFS-189737

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 647-658, 2022

Authors: Jain, Achin | Jain, Vanita

Article Type: Research Article

Abstract: This paper presents a Hybrid Feature Selection Technique for Sentiment Classification. We have used a Genetic Algorithm and a combination of existing Feature Selection methods, namely: Information Gain (IG), CHI Square (CHI), and GINI Index (GINI). First, we have obtained features from three different selection approaches as mentioned above and then performed the UNION SET Operation to extract the reduced feature set. Then, Genetic Algorithm is applied to optimize the feature set further. This paper also presents an Ensemble Approach based on the error rate obtained different domain datasets. To test our proposed Hybrid Feature Selection and Ensemble Classification approach, …we have considered four Support Vector Machine (SVM) classifier variants. We have used UCI ML Datasets of three domains namely: IMDB Movie Review, Amazon Product Review and Yelp Restaurant Reviews. The experimental results show that our proposed approach performed best in all three domain datasets. Further, we also presented T -Test for Statistical Significance between classifiers and comparison is also done based on Precision, Recall, F1-Score, AUC and model execution time. Show more

Keywords: Classification, sentiment analysis, genetic algorithm, support vector machine, machine learning

DOI: 10.3233/JIFS-189738

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 659-668, 2022

Authors: Malik, Hasmat | Almutairi, Abdulaziz | Alotaibi, Majed A.

Article Type: Research Article

Abstract: In the modern electrical power system network (EPSN), the power quality disturbances (PSDs) are the serious issue for the power engineer to maintain the uninterrupted and reliable power supply. Generally, PQDs are generated due to non-linear loading conditions, perturb loading and other occurrences such as transient, harmonics, sag, swell and interruptions. These problems of PQDs effect the power demand mapping problem, which effect the reliability and stability of the EPSN operating condition. In this study, a novel approach for PQDs diagnosis (PQDD) is proposed, which includes real-time data generation, data pre-processing, feature extraction, feature selection, intelligent model development for PQDD. …Data decomposition approach of EMD is utilized to generate the feature vector of IMFs. These features are utilized as an input variables to the intelligent classifiers. In this study, PQDD is analyzed based on SVM method and obtained results are compared with conventional AI method of LVQ-NN. The results represent the higher acceptability of the proposed approach with diagnosis accuracy of 99.98% (training phase), 93.11% (testing phase) for SVM and 92.56% (training phase) and 91.0% (testing phase) for LVQ-NN based PQDD method. Show more

Keywords: Data pre-processing, diagnosis, EMD, LVQ, feature extraction, SVM

DOI: 10.3233/JIFS-189739

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 669-678, 2022

Authors: Sharma, Ajit Kumar | Bhushan, Bharat

Article Type: Research Article

Abstract: The present work represents the implementation of the various fuzzy controller with robust sliding mode control (SMC) technique on a nonlinear system considering various external disturbances and model uncertainties. The nonlinear system considered here is a single link inverted pendulum. The proposed work combines the advantages of the sliding mode controlling technique and fuzzy logic controller. A set of linguistic rules are designed in fuzzy logic control, which causes the system to be chattering free. Parameters of the nonlinear system are adjusted according to fuzzy adaptive laws, while the uncertainties of the nonlinear system have been approximated using a fuzzy …system. Various types of controller based on fuzzy sliding mode, like approximation based sliding mode control technique; equivalent control based fuzzy sliding mode technique, and switch-gain regulation based sliding mode control methods have been implemented here. A comparative analysis of various methods is also have been discussed. Show more

Keywords: Sliding mode control (SMC), inverted pendulum, adaptive control, fuzzy control, fuzzy sliding mode control (FSMC)

DOI: 10.3233/JIFS-189740

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 679-688, 2022

Authors: Tabrez, Md | Sadhu, Pradip Kumar | Iqbal, Atif | Husain, Mohammed Aslam | Bakhsh, Farhad Ilahi | Singh, S. P.

Article Type: Research Article

Abstract: Impedance mismatching between different phases of a multiphase transformer is generally observed e.g., in a three-phase to seven-phase transformer, due to an unequal number of turns in different coils. This mismatching introduces error in the study of per phase equivalent circuit diagrams as well as induces an imbalance in output voltages and currents. Therefore, it is a challenging task to develop a per-phase equivalent circuit for the secondary and primary sides (In some cases) too. This paper proposes an artificial intelligence optimization technique like PSO based modeling of the per-phase equivalent circuit of the secondary side. This paper deals with …the modeling and simulation of a three-phase to seven-phase power transformer using Artificial Intelligence technique like particle swarm optimization (PSO) and Genetic Algorithm (GA). The proposed model is optimized through PSO and GA algorithms and tested for minimum voltage error in each phase. The proposed model is designed and the objective function is optimized by PSO & GA in MATLAB environment. It is found that the optimized model can be effectively implemented as a per-phase equivalent circuit for the secondary side. Show more

Keywords: Genetic algorithm, multiphase, particle swarm optimization, transformer, seven-phase

DOI: 10.3233/JIFS-189741

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 689-698, 2022

Authors: Sanaullah, Asif | Fatema, Nuzhat | Ather, Muhammad | Sanaullah, Arif | Malik, H.

Article Type: Research Article

Abstract: The purpose of this study was to examine the relationship of relationship benefit and commitment in developing customer loyalty first and then to develop the intelligent model to predict the customer loyalty. Survey methodology was used to gather data from three different service sectors based on the classification by Bowen. A sample of 600 customers and responses were collected randomly from the front desk of services. Regression analysis by Using SPSS 20 was applied to analyze the data collected. The findings of the study revealed that relationship benefit and commitment had direct positive influence on customer loyalty. Furthermore the commitment …of customer towards an organization is instrumental in developing loyalty. After performing the advance data analytics, ANN model was developed to predict the loyalty, which can be utilized to prepare the further directions and road map for service industry. Obtained results reveals that proposed machine intelligence approach is very useful for service industry for short-term as well long-term future planning. Show more

Keywords: Relationship benefit (RB), customer loyalty (CL), confidence benefit (CB), special treatment benefit (STB), social benefit (SB), affective commitment (AC), normative commitment (NC) and calculative commitment CC, ANN

DOI: 10.3233/JIFS-189742

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 699-712, 2022

Authors: Mohanta, Bhabendu Kumar | Jena, Debasish | Mohapatra, Niva | Ramasubbareddy, Somula | Rawal, Bharat S.

Article Type: Research Article

Abstract: Smart city has come a long way since the development of emerging technology like Information and communications technology (ICT), Internet of Things (IoT), Machine Learning (ML), Block chain and Artificial Intelligence. The Intelligent Transportation System (ITS) is an important application in a rapidly growing smart city. Prediction of the automotive accident severity plays a very crucial role in the smart transportation system. The main motive behind this research is to determine the specific features which could affect vehicle accident severity. In this paper, some of the classification models, specifically Logistic Regression, Artificial Neural network, Decision Tree, K-Nearest Neighbors, and Random …Forest have been implemented for predicting the accident severity. All the models have been verified, and the experimental results prove that these classification models have attained considerable accuracy. The paper also explained a secure communication architecture model for secure information exchange among all the components associated with the ITS. Finally paper implemented web base Message alert system which will be used for alert the users through smart IoT devices. Show more

Keywords: Intelligent data analytics, machine learning, intelligent transportation system, secure communication, internet of things

DOI: 10.3233/JIFS-189743

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 713-725, 2022