Siva Sankari Subbiah¹, Senthil Kumar Paramasivan^2,*, Karmel Arockiasamy³, Saminathan Senthivel⁴, Muthamilselvan Thangavel²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3829-3844, 2023, DOI:10.32604/iasc.2023.030480

Abstract Wind speed forecasting is important for wind energy forecasting. In the modern era, the increase in energy demand can be managed effectively by forecasting the wind speed accurately. The main objective of this research is to improve the performance of wind speed forecasting by handling uncertainty, the curse of dimensionality, overfitting and non-linearity issues. The curse of dimensionality and overfitting issues are handled by using Boruta feature selection. The uncertainty and the non-linearity issues are addressed by using the deep learning based Bi-directional Long Short Term Memory (Bi-LSTM). In this paper, Bi-LSTM with Boruta feature selection named BFS-Bi-LSTM is proposed… More >

V. Krishnakumar^*, R. Asokan

Computer Systems Science and Engineering, Vol.45, No.1, pp. 985-1000, 2023, DOI:10.32604/csse.2023.029189

Abstract Wireless sensor Mobile ad hoc networks have excellent potential in moving and monitoring disaster area networks on real-time basis. The recent challenges faced in Mobile Ad Hoc Networks (MANETs) include scalability, localization, heterogeneous network, self-organization, and self-sufficient operation. In this background, the current study focuses on specially-designed communication link establishment for high connection stability of wireless mobile sensor networks, especially in disaster area network. Existing protocols focus on location-dependent communications and use networks based on typically-used Internet Protocol (IP) architecture. However, IP-based communications have a few limitations such as inefficient bandwidth utilization, high processing, less transfer speeds, and excessive memory… More >

Abhishek Sharma¹, Sushank Chaudhary^2,*, Jyoteesh Malhotra³, Muhammad Saadi⁴, Sattam Al Otaibi⁵, Lunchakorn Wuttisittikulkij²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5399-5410, 2022, DOI:10.32604/cmc.2022.031173

Abstract Recent reports from World Health Organization (WHO) show the impact of human negligence as a serious concern for road accidents and casualties worldwide. There are number of reasons which led to this negligence; hence, need of intelligent transportation system (ITS) gains more attention from researchers worldwide. For achieving such autonomy different sensors are involved in autonomous vehicles which can sense road conditions and warn the control system about possible hazards. This work is focused on designing one such sensor system which can detect and range multiple targets under the impact of adverse atmospheric conditions. A high-speed Linear Frequency Modulated Continuous… More >

Yousef Ibrahim Daradkeh^1,*, Volodymyr Gorokhovatskyi², Iryna Tvoroshenko², Medien Zeghid^3,4

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6069-6084, 2022, DOI:10.32604/cmc.2022.030254

Abstract The problem of image recognition in the computer vision systems is being studied. The results of the development of efficient classification methods, given the figure of processing speed, based on the analysis of the segment representation of the structural description in the form of a set of descriptors are provided. We propose three versions of the classifier according to the following principles: “object–etalon”, “object descriptor–etalon” and “vector description of the object–etalon”, which are not similar in level of integration of researched data analysis. The options for constructing clusters over the whole set of descriptions of the etalon database, separately for… More >

V. Jesus Bobin^*, M. MarsalineBeno

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2493-2511, 2023, DOI:10.32604/iasc.2023.024679

Abstract Three-phase induction motors are becoming increasingly utilized in industrial field due to their better efficiency and simple manufacture. The speed control of an induction motor is essential in a variety of applications, but it is difficult to control. This research analyses the three-phase induction motor’s performance using field-oriented control (FOC) and direct torque control (DTC) techniques. The major aim of this work is to provide a critical evaluation of developing a simple speed controller for induction motors with improving the performance of Induction Motor (IM). For controlling a motor, different optimization approaches are accessible; in this research, a Fuzzy Logic… More >

Enhua Li^*

Molecular & Cellular Biomechanics, Vol.19, No.3, pp. 141-149, 2022, DOI:10.32604/mcb.2022.018558

Abstract This study aims to analyze the difference in biomechanical properties of football players at different levels when kicking the football with the inner edge of the instep. Before the experiment, ten football players were selected; five were higher than the national level (group A), and the other five players were lower than the national level II (group B). During the experiment, the motion process was captured by a high-speed camera for biomechanical analysis. It was found that in group A, the thigh and leg swung in less time and larger amplitude, the acceleration of backswing and forward swing of the… More >

R. S. Preethishri^*, J. Anitha Roseline, K. Murugesan, M. Senthil Kumaran

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 997-1014, 2023, DOI:10.32604/iasc.2023.025510

Abstract The Power Factor Correction (PFC) in Switched Reluctance (SR) motor is discussed in this article. The SR motors are applicable for multiple applications like electric vehicles, wind mills, machineries etc. The doubly salient structure of SR motor causes the occurrence of torque ripples, which affects the power factor of the motor. To improve the power quality, the power factor has to be corrected and the ripples have to be minimized. In order to achieve these objectives, a novel power factor correction (PFC) method is proposed in this work. Here, the conventional Diode Bridge Rectifier (DBR) is replaced by a Bridgeless… More >

Wenzheng Yu¹, Yang Gao¹, Zhengyu Yuan¹, Xin Yao^1,*, Mingxuan Zhu¹, Hanxiaoya Zhang²

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 563-576, 2022, DOI:10.32604/cmc.2022.027008

Abstract

Poisson-Gumbel joint distribution model uses maximum wind speed corresponding to multiple typhoons to construct sample sequence. Thresholds are usually used to filter sample sequences to make them more consistent with Poisson distribution. However, few studies have discussed the threshold setting and its impact on Poisson-Gumbel joint distribution model. In this study, a sample sequence based on the data of Qinzhou meteorological station from 2005 to 2018 were constructed. We set 0%, 5%, 10%, 20% and 30% gradient thresholds. Then, we analyzed the influence of threshold change on the calculation results of maximum wind speed in different return periods. The results… More >

Aodi Fu¹, Mingxuan Zhu², Wenzheng Yu^1,*, Xin Yao¹, Hanxiaoya Zhang³

Journal on Big Data, Vol.4, No.1, pp. 77-86, 2022, DOI:10.32604/jbd.2022.027477

Abstract In 2014, Typhoon Rammasun invaded Qinzhou, Guangxi, causing damage to the wind tower sensor at 80 m in Qinzhou. In order to restore the wind speed at 80 m at that time, this paper was based on the hourly average wind speed data of the wind tower and meteorological station from 2017–2019, and constructed the wind speed related model of Meteorological Station and the wind measuring tower in Qinzhou, Moreover, this paper Based on the hourly average wind speed data of Qinzhou Meteorological Station in 2014, Restored the hourly average wind speed of the anemometer tower during Rammasun landfalled. The results showed… More >

Yingnan Zhao^1,*, Peiyuan Ji¹, Fei Chen¹, Guanlan Ji¹, Sunil Kumar Jha²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1001-1016, 2022, DOI:10.32604/iasc.2022.027710

Abstract This paper proposes a spatio-temporal model (VCGA) based on variational mode decomposition (VMD) and attention mechanism. The proposed prediction model combines a squeeze-and-excitation network to extract spatial features and a gated recurrent unit to capture temporal dependencies. Primarily, the VMD can reduce the instability of the original wind speed data and the attention mechanism functions to strengthen the impact of important information. In addition, the VMD and attention mechanism act to avoid a decline in prediction accuracy. Finally, the VCGA trains the decomposition result and derives the final results after merging the prediction result of each component. Contrasting experiments for… More >