Journal of Intelligent & Fuzzy Systems - Volume 41, issue 5

Authors: Vasudevan, Nisha | Venkatraman, Vasudevan | Ramkumar, A | Sheela, A

Article Type: Research Article

Abstract: Smart grid is a sophisticated and smart electrical power transmission and distribution network, and it uses advanced information, interaction and control technologies to build up the economy, effectiveness, efficiency and grid security. The accuracy of day-to-day power consumption forecasting models has an important impact on several decisions making, such as fuel purchase scheduling, system security assessment, economic capacity generation scheduling and energy transaction planning. The techniques used for improving the load forecasting accuracy differ in the mathematical formulation as well as the features used in each formulation. Power utilization of the housing sector is an essential component of the overall …electricity demand. An accurate forecast of energy consumption in the housing sector is quite relevant in this context. The recent adoption of smart meters makes it easier to access electricity readings at very precise resolutions; this source of available data can, therefore, be used to build predictive models., In this study, the authors have proposed Prophet Forecasting Model (PFM) for the application of forecasting day-ahead power consumption in association with the real-time power consumption time series dataset of a single house connected with smart grid near Paris, France. PFM is a special type of Generalized Additive Model. In this method, the time series power consumption dataset has three components, such as Trend, Seasonal and Holidays. Trend component was modelled by a saturating growth model and a piecewise linear model. Multi seasonal periods and Holidays were modelled with Fourier series. The Power consumption forecasting was done with Autoregressive Integrated Moving Average (ARIMA), Long Short Term Neural Memory Network (LSTM) and PFM. As per the comparison, the improved RMSE, MSE, MAE and RMSLE values of PFM were 0.2395, 0.0574, 0.1848 and 0.2395 respectively. From the comparison results of this study, the proposed method claims that the PFM is better than the other two models in prediction, and the LSTM is in the next position with less error. Show more

Keywords: Energy management, smart home, energy forecast, power management, efficiency

DOI: 10.3233/JIFS-189886

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5665-5676, 2021

Authors: Renugadevi, T. | Geetha, K.

Article Type: Research Article

Abstract: Management of IT services is rapidly adapting to the cloud computing environment due to optimized service delivery models. Geo distributed cloud data centers act as a backbone for providing fundamental infrastructure for cloud services delivery. Conversely, their high growing energy consumption rate is the major problem to be addressed. Cloud providers are in a hunger to identify different solutions to tackle energy management and carbon emission. In this work, a multi-cloud environment is modeled as geographically distributed data centers with varying solar power generation corresponding to its location, electricity price, carbon emission, and carbon tax. The energy management of the …workload allocation algorithm is strongly dependent on the nature of the application considered. The task deadline and brownout information is used to bring in variation in task types. The renewable energy-aware workload allocation algorithm adaptive to task nature is proposed with migration policy to explore its impact on carbon emission, total energy cost, brown and renewable power consumption. Show more

Keywords: Sustainable data centers, carbon footprint, brownout, migration, green energy, workload allocation

DOI: 10.3233/JIFS-189887

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5677-5689, 2021

Authors: Preethi, D. | Vimala, J.

Article Type: Research Article

Abstract: This paper introduces the concept of homomorphism on fuzzy hyperlattice ordered group ( FHLOG ) . It studies how the binary and the fuzzy hyperoperations of a FHLOG can be transformed into the binary and the fuzzy hyperoperations of another FHLOG . The notion of fuzzy hypercongruence relation on FHLOG is also defined. The paper also establishes the redox reaction of copper, gold and americium forms three FHLOG s. Besides, homomorphism and composition function of FHLOG …s using the redox reactions are developed. Therefore, the paper develops a relation among three different metal’s redox reactions in which the binary and the fuzzy hyperoperations, are preserved. Show more

Keywords: Lattice ordered group, fuzzy lattice ordered group, fuzzy hyperlattice, fuzzy hyperlattice ordered group, homomorphism, redox reactions

DOI: 10.3233/JIFS-189888

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5691-5699, 2021

Authors: Alpana, | Chand, Satish | Mohapatra, Subrajeet | Mishra, Vivek

Article Type: Research Article

Abstract: Coal is the mixture of organic matters, called as macerals, and inorganic matters. Macerals are categorized into three major groups, i.e., vitrinite, inertinite, and liptinite. The maceral group identification serves an important role in coking and non-coking coal processes that are used mainly in steel and iron industries. Hence, it becomes important to efficiently characterize these maceral groups. Currently, industries use the optical polarized microscope to distinguish the maceral groups. However, the microscopical analysis is a manual method which is time-consuming and provides subjective outcome due to human interference. Therefore, an automated approach that can identify the maceral groups accurately …in less processing time is strongly needed in industries. Computer-based image analysis methods are revolutionizing the industries because of its accuracy and efficacy. In this study, an intelligent maceral group identification system is proposed using markov-fuzzy clustering approach. This approach is an integration of fuzzy sets and the markov random field, which is employed towards maceral group identification in a clustering framework. The proposed model shows better results when compared with the standard cluster-based segmentation techniques. The results from the suggested model have also been validated against the outcome of manual methods, and the feasibility is tested using performance metrics. Show more

Keywords: Coal, macerals, image segmentation, clustering, fuzzy sets, markov random field

DOI: 10.3233/JIFS-189889

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5701-5707, 2021

Authors: Rajareega, S. | Vimala, J.

Article Type: Research Article

Abstract: This paper introduces some new operations on complex intuitionistic fuzzy lattice ordered groups such as sum, product, bounded product, bounded difference and disjoint sum, and verifying its pertinent properties. The research exhibits the CIFS-COPRAS algorithm in a complex intuitionistic fuzzy soft set environment. This method was furthermore applied for the equipment selection process.

Keywords: Complex intuitionistic fuzzy soft sets, complex intuitionistic fuzzy soft lattice ordered group, COPRAS, C-COPRAS, equipment selection process

DOI: 10.3233/JIFS-189890

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5709-5718, 2021

Authors: Nagaballi, Srinivas | Kale, Vijay S.

Article Type: Research Article

Abstract: The advent of distributed energy resources is undoubtedly transforming the nature of the electric power system. The crisis of conventional energy sources and their environmental effects resulted in the integration of Distributed Generators (DGs) into the distribution system. Simultaneous application of optimum network reconfiguration, DGs, and Distribution Static Compensator (DSTATCOM) unit’s placement in the Radial Distribution Systems (RDS) comes with a raft of technical, economic, and environmental benefits. Benefits include improved power quality, reliability, stability, mitigation of power losses, and voltage profile improvement. In this paper, the combinational process of optimal deployment of DGs and DSTATCOM units in RDS with …suitable network reconfiguration to achieve positive benefits has been analyzed. A recent metaphor-less based Artificial Intelligence (AI) technique named the Rao-1 method is employed to overcome this combinational nonlinear optimization problem. The objective functions are to mitigate the power losses, enhance the voltage profile, and voltage stability index of the RDS considering the net economic cost-benefit to the distribution utility. The simulation study of this pragmatic approach problem is carried out on IEEE 33-bus RDS. The comparison of the results obtained by the Rao-1 method with other existing meta-heuristic optimization methods has been made to show its efficacy. Show more

Keywords: Artificial intelligence techniques, distributed generation, DSTATCOM, power losses, reconfiguration, voltage profile, stability, techno-economic benefits

DOI: 10.3233/JIFS-189891

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5719-5729, 2021

Authors: Jeyanthi, R. | Sahithi, Madugula | Sireesha, N.V.L. | Srinivasan, Mangala Sneha | Devanathan, Sriram

Article Type: Research Article

Abstract: In process industries, measurements usually contain errors due to the improper instrumental variation, physical leakages in process streams and nodes, and inaccurate recording/reporting. Thus, these measurements violate the laws of conservation, and do not conform to process constraints. Data reconciliation (DR) is used to resolve the difference between measurements and constraints. DR is also used in reducing the effect of random errors and more accurately estimating the true values. A multivariate technique that is used to obtain estimates of true values while preserving the most significant inherent variation is Principal Component Analysis (PCA). PCA is used to reduce the dimensionality …of the data with minimum information loss. In this paper, two new DR techniques are proposed moving-average PCA (MA-PCA) and exponentially weighted moving average PCA (EWMA-PCA) to improve the performance of DR and obtain more accurate and consistent data. These DR techniques are compared based on RMSE. Further, these techniques are analyzed for different values of sample size, weighting factor, and variances. Show more

Keywords: Data reconciliation, MA-PCA, EWMA-PCA

DOI: 10.3233/JIFS-189892

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5731-5736, 2021

Authors: Krishnamoorthy, Amrutha | Sindhura, Vijayasimha Reddy | Gowtham, Devarakonda | Jyotsna, C. | Amudha, J.

Article Type: Research Article

Abstract: Extraction of eye gaze events is highly dependent on automated powerful software that charges exorbitant prices. The proposed open-source intelligent tool StimulEye helps to detect and classify eye gaze events and analyse various metrics related to these events. The algorithms for eye event detection in use today heavily depend on hand-crafted signal features and thresholding, which are computed from the stream of raw gaze data. These algorithms leave most of their parametric decisions on the end user which might result in ambiguity and inaccuracy. StimulEye uses deep learning techniques to automate eye gaze event detection which neither requires manual decision …making nor parametric definitions. StimulEye provides an end to end solution which takes raw streams of data from an eye tracker in text form, analyses these to classify the inputs into the events, namely saccades, fixations, and blinks. It provides the user with insights such as scanpath, fixation duration, radii, etc. Show more

Keywords: Eye tracking, fixations, saccades, scanpath, deep learning

DOI: 10.3233/JIFS-189893

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5737-5745, 2021

Authors: Pradhan, Rosy | Khan, Mohammad Rafique | Sethy, Prabir Kumar | Majhi, Santosh Kumar

Article Type: Research Article

Abstract: The field of optimization science is proliferating that has made complex real-world problems easy to solve. Metaheuristics based algorithms inspired by nature or physical phenomena based methods have made its way in providing near-ideal (optimal) solutions to several complex real-world problems. Ant lion Optimization (ALO) has inspired by the hunting behavior of antlions for searching for food. Even with a unique idea, it has some limitations like a slower rate of convergence and sometimes confines itself into local solutions (optima). Therefore, to enhance its performance of classical ALO, quantum information theory is hybridized with classical ALO and named as QALO …or quantum theory based ALO. It can escape from the limitations of basic ALO and also produces stability between processes of explorations followed by exploitation. CEC2017 benchmark set is adopted to estimate the performance of QALO compared with state-of-the-art algorithms. Experimental and statistical results demonstrate that the proposed method is superior to the original ALO. The proposed QALO extends further to solve the model order reduction (MOR) problem. The QALO based MOR method performs preferably better than other compared techniques. The results from the simulation study illustrate that the proposed method effectively utilized for global optimization and model order reduction. Show more

Keywords: Antlion optimization, quantum information theory, model order reduction, metahueristic optimization, CEC benchmark

DOI: 10.3233/JIFS-189894

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5747-5757, 2021

Authors: George, Sheeja P. | Isaac, Johney | Philip, Jacob

Article Type: Research Article

Abstract: A higher operating frequency is desirable for Surface Acoustic Wave (SAW) based sensors as they become more sensitive at high frequencies. The acoustic wave gets more confined near the surface at high frequencies and become more sensitive to the external stimulations. This makes SAW devices a suitable device for sensing gaseous state chemicals. SAW devices have become the basic building block of wireless sensor networks with its advantages enabling remote sensing. In this paper, a SAW based Hydrogen sensor is realized through the Finite Element Analysis tool ANSYS. Hydrogen even though has a significant role in many industries, its explosive …nature demands constant monitoring. SAW delay line made up of XY-LiNbO3 as substrate with a thin layer of Palladium coated along the delay length as the sensing element is modeled. Palladium with its high affinity for Hydrogen absorbs the same and undergoes changes in properties like density and stiffness. This disturbs the surface wave propagation and in turn, affects the operating frequency which is the sensor response parameter. The frequency shift of 1.91 MHz for Hydrogen concentration of 0.3 a.f. as compared to 0.49 MHz with YZ- LiNbO3. The operating frequency also shifts to a higher range as the acoustic velocity of the substrate increases. Show more

Keywords: SAW, gas sensor, wireless sensor, FEM, ANSYS

DOI: 10.3233/JIFS-189895

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5759-5768, 2021