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

Authors: Asim, Mohammed | Agrawal, Piyush | Tariq, Mohd | Alamri, Basem

Article Type: Research Article

Abstract: Under partial shading conditions (PSC), most traditional maximum power point tracking (MPPT) techniques may not adopt GP (global peak). These strategies also often take a considerable amount of time to reach a full power point (MPP). Such obstacles can be eliminated by the use of metaheuristic strategies. This paper shows, in partial shading conditions, the MPPT technique for the photovoltaic system using the Bat Algorithm (BA). Simulations have been performed in the MATLAB® /Simulink setting to verify the efficacy of the proposed method. In MPPT applications, the results of the simulations emphasize the precision of the proposed technique. The algorithm …is also simple and efficient, on a low-cost microcontroller, it could be implemented. Hardware in Loop (HIL) validation is performed, with a Typhoon HIL 402 setup. Show more

Keywords: Photovoltaic system, partial shading conditions, maximum power point tracking, Bat algorithm

DOI: 10.3233/JIFS-189754

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 851-859, 2022

Authors: Sarita, Kumari | Devarapalli, Ramesh | Kumar, Sanjeev | Malik, H. | García Márquez, Fausto Pedro | Rai, Pankaj

Article Type: Research Article

Abstract: Online condition monitoring and predictive maintenance are crucial for the safe operation of equipments. This paper highlights an unsupervised statistical algorithm based on principal component analysis (PCA) for the predictive maintenance of industrial induced draft (ID) fan. The high vibration issues in ID fans cause the failure of the impellers and, sometimes, the complete breakdown of the fan-motor system. The condition monitoring system of the equipment should be reliable and avoid such a sudden breakdown or faults in the equipment. The proposed technique predicts the fault of the ID fan-motor system, being applicable for other rotating industrial equipment, and also …for which the failure data, or historical data, is not available. The major problem in the industry is the monitoring of each and every machinery individually. To avoid this problem, three identical ID fans are monitored together using the proposed technique. This helps in the prediction of the faulty part and also the time left for the complete breakdown of the fan-motor system. This helps in forecasting the maintenance schedule for the equipment before breakdown. From the results, it is observed that the PCA-based technique is a good fit for early fault detection and getting alarmed under fault condition as compared with the conventional methods, including signal trend and fast Fourier transform (FFT) analysis. Show more

Keywords: Machine learning, industry 4.0, PCA, condition monitoring, predictive maintenance, preprocessing

DOI: 10.3233/JIFS-189755

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 861-872, 2022

Authors: Alzubi, Omar A.

Article Type: Research Article

Abstract: Industrial Wireless Sensor Network (IWSN) includes numerous sensor nodes that collect data about target objects and transmit to sink nodes (SN). During data transmission among nodes, intrusion detection is carried to improve data security and privacy. Intrusion detection system (IDS) examines the network for intrusions based on user activities. Several works have been done in the field of intrusion detection and different measures are carried out to increase data security from the issues related to black hole, Sybil attack, Worm hole, identity replication attack and etc. In various existing approaches, secure data transmission is not achieved, therefore resulted in compromising …the security and privacy of IWSNs. Accurate intrusion detection is still challenging task in terms of improving security and intrusion detection rate. In order to improve intrusion detection rate (IDR) with minimum time, generalized Frechet Hyperbolic Deep and Dirichlet Secured (FHD-DS) data communication model is introduced. At first, Frechet Hyperbolic Deep Traffic (FHDT) feature extraction method is designed to extract more relevant network activities and inherent traffic features. With the help of extracted features, anomalous or normal data is predicted. Followed by Statistical Dirichlet Anomaly-based Intrusion Detection model is applied to discover intrusion. Here, Dirichlet distribution is evaluated to attain secure data transmission and significantly detect intrusions in WSNs. Experimental evaluation is carried out with KDD cup 99 dataset on factors such as IDR, intrusion detection time (IDT) and data delivery rate (DDR). The observed results show that the generalized FHD-DS data communication method achieves higher IDR with minimum time. Show more

Keywords: Deep learning, intrusion detection, industrial wireless sensor networks, IWSN security, Fréchet hyperbolic, statistical dirichlet distribution, machine learning, security

DOI: 10.3233/JIFS-189756

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 873-883, 2022

Authors: Alsaidan, Ibrahim | Rizwan, Mohammad | Alaraj, Muhannad

Article Type: Research Article

Abstract: The rapid advancements in the technology, increase in comfort levels, movement of population to urban areas, depletion of fossil fuels and increasing greenhouse gas emissions have invigorated the use of renewable energy resources for power generation in the last few years. The major renewable energy resources which have potential to fulfill the requirements includes solar energy, wind energy, small hydro and biomass etc. Among these major resources, solar energy-based technology is considered as one of the fastest growing technology because of its various advantages and ubiquitous availability of the resources. However, there are certain challenges in the utilization of solar …energy for power generation because of various uncertainties in the atmosphere. As a result, the power generated from solar based power plants is fluctuating in nature which is not desirable. Therefore, the utilities are adopting the smart grid approach which has ability to integrate the solar power plants efficiently and the solar energy forecasting is one of the essential tools for this new model. In this paper, AI based techniques are utilized to forecast solar energy using high quality measured solar irradiance data. The forecasting accuracy of the developed models is evaluated based on statistical indices such as absolute relative error and mean absolute percentage error. The results obtained from the developed models are compared to observe the forecasting ability and performance with the high-quality measured data and found accurate. Show more

Keywords: Artificial intelligence techniques, solar energy forecasting, smart energy management, intelligent systems, sustainable power generation

DOI: 10.3233/JIFS-189757

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 885-896, 2022

Authors: Bisht, Vimal Singh | Hasan, Mashhood | Malik, Hasmat | Sunori, Sandeep

Article Type: Research Article

Abstract: For estimation of the RUL (Remaining useful life) of Lithium ion battery we are required to do its health assessment using online facilities. For identifying the health of a battery its internal resistance and storage capacity plays the major role. However the estimation of both these parameters is not an easy job and requires lot of computational work to be done. So to overcome this constraint an easy alternate way is simulated in the paper through which we can estimate the RUL. For formation of a linear relationship between health index of the battery (HI) and its actual capacity used …of power transformation method is done and later on to validate the result a comparison study is done with Pearson & Spearman methods. Transformed value of Health Index is used for developing a neural network. The results demonstrated in the paper shows the feasibility of the proposed technique resulting in great saving of time Show more

Keywords: Remaining-useful-life, health indicator, lithium-Ion battery, Box-Cox, data-driven

DOI: 10.3233/JIFS-189758

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 897-907, 2022

Authors: Malik, Shaily | Bansal, Poonam

Article Type: Research Article

Abstract: The real-world data is multimodal and to classify them by machine learning algorithms, features of both modalities must be transformed into common latent space. The high dimensional common space transformation of features lose their locality information and susceptible to noise. This research article has dealt with this issue of a semantic autoencoder and presents a novel algorithm with distinct mapped features with locality preservation into a commonly hidden space. We call it discriminative regularized semantic autoencoder (DRSAE). It maintains the low dimensional features in the manifold to manage the inter and intra-modality of the data. The data has multi labels, …and these are transformed into an aware feature space. Conditional Principal label space transformation (CPLST) is used for it. With the two-fold proposed algorithm, we achieve a significant improvement in text retrieval form image query and image retrieval from the text query. Show more

Keywords: Semantic autoencoder, hypergraph, twofold validation, cross model retrieval

DOI: 10.3233/JIFS-189759

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 909-917, 2022

Authors: Srivastava, Vishal | Srivastava, Smriti

Article Type: Research Article

Abstract: Ball and beam is a popular benchmark problem in control engineering. Various control strategies have been proposed on ball & beam system in literature, In this paper, hybrid optimization algorithms have been implemented on PID controller to control ball position and beam angle. Hybrid algorithms combine exploration and exploitation ability of individual algorithm and find optimized value of performance index. In this paper, two hybrid algorithms namely PSO-GSA and PSO-GWO are used to tune controller parameters which in turn improve the system performance. Simulation results show effective and efficient improvement in system performance with these hybrid algorithms. To analyze the …performance of these algorithms, time domain parameters and mean square error (MSE) has been taken as performance index. A comparative study of these algorithms with that of individual algorithms namely PSO, GWO, GSA has also been done. Show more

Keywords: Ball and beam, particle swarm optimization (PSO), gravitational search algorithm (GSA), grey wolf optimization (GWO), mean square error (MSE), robustness

DOI: 10.3233/JIFS-189760

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 919-928, 2022

Authors: Gupta, Sangeeta | Varshney, Pragya | Srivastava, Smriti

Article Type: Research Article

Abstract: This paper proposes a scheme to synchronize fractional order chaotic systems employing fractional PID controller. The parameters of FOPID are tuned using Swarm based optimization techniques, viz.: Whale optimization algorithm and Particle swarm optimization techniques. To assert the complete synchronization, master-slave method has been implemented. Chaotic systems are highly dependent upon initial conditions and parameter perturbations. Therefore, taking these properties into consideration, synchronization of two identical fractional order financial chaotic systems is performed with distinct initial conditions. To show the efficacy of the proposed method, analysis is performed for orders between 0 to 1, and also for sensitivity to initial …conditions. Show more

Keywords: Fractional order chaotic system (FOCS), fractional order financial chaotic system (FOFCS), whale optimization algorithm (WOA), particle swarm optimization (PSO), proportional-integral-derivative (PID) controller, fractional order PID (FOPID) controller

DOI: 10.3233/JIFS-189761

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 929-942, 2022

Authors: Tyagi, Shikhar | Chawla, Bhavya | Jain, Rupav | Srivastava, Smriti

Article Type: Research Article

Abstract: Single biometric modalities like facial features and vein patterns despite being reliable characteristics show limitations that restrict them from offering high performance and robustness. Multimodal biometric systems have gained interest due to their ability to overcome the inherent limitations of the underlying single biometric modalities and generally have been shown to improve the overall performance for identification and recognition purposes. This paper proposes highly accurate and robust multimodal biometric identification as well as recognition systems based on fusion of face and finger vein modalities. The feature extraction for both face and finger vein is carried out by exploiting deep convolutional …neural networks. The fusion process involves combining the extracted relevant features from the two modalities at score level. The experimental results over all considered public databases show a significant improvement in terms of identification and recognition accuracy as well as equal error rates. Show more

Keywords: Multimodal biometrics, face, finger vein, convolutional neural network, score level fusion

DOI: 10.3233/JIFS-189762

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 943-955, 2022

Authors: Devarapalli, Ramesh | Venkateswara Rao, B. | Dey, Bishwajit | Vinod Kumar, K. | Malik, H. | García Márquez, Fausto Pedro

Article Type: Research Article

Abstract: Nowadays, improvement in power system performance is essential to obtaine economic and technical benifits. To achieve this, optimize the large number of parameters in the system based on optimal power flow(OPF). For solving OPF problem efficiently, it needs robust and fast optimization techniques. This paper proposes the application of a newly developed hybrid Whale and Sine Cosine optimization algorithm to solve the OPF. It has been implemented for optimization of the control variables. The reduction of true power generation cost, emission, true power losses, and voltage deviation are considered as different objectives. The hybrid Whale and Sine Cosine optimization is …validated by solving OPF problem with various intentions using IEEE30 bus system. To varidate the proposed technique, the results obtained from this are compared with other methods in the literature. The robustness achieved with the proposed algorithm has been analyzed for the considered OPF problem using statistical analysis and whisker plots. Show more

Keywords: Optimal power flow, sine cosine optimization, voltage deviation, whale optimization

DOI: 10.3233/JIFS-189763

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 957-967, 2022