S. Navaneetha Krishnan¹, P. Sundara Vadivel^2,*, D. Yuvaraj³, T. Satyanarayana Murthy⁴, Sree Jagadeesh Malla⁵, S. Nachiyappan⁶, S. Shanmuga Priya⁷

Computer Systems Science and Engineering, Vol.43, No.1, pp. 17-26, 2022, DOI:10.32604/csse.2022.021590 - 23 March 2022

Abstract Wireless Sensor Networks (WSN) are commonly used to observe and monitor precise environments. WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments. The base station received the amount of data collected by the numerous sensors. The current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large scale. The Trust-Based Adaptive Acknowledgement (TRAACK) Intrusion-Detection System for Wireless Sensor Networks (WSN) is described based on the number of active positive deliveries and The Kalman filter used in Modified More >

R. S. Latha^1,*, B. Saravana Balaji², Nebojsa Bacanin³, Ivana Strumberger³, Miodrag Zivkovic³, Milos Kabiljo³

Computer Systems Science and Engineering, Vol.43, No.1, pp. 317-332, 2022, DOI:10.32604/csse.2022.020487 - 23 March 2022

Abstract Big data are regarded as a tremendous technology for processing a huge variety of data in a short time and with a large storage capacity. The user’s access over the internet creates massive data processing over the internet. Big data require an intelligent feature selection model by addressing huge varieties of data. Traditional feature selection techniques are only applicable to simple data mining. Intelligent techniques are needed in big data processing and machine learning for an efficient classification. Major feature selection algorithms read the input features as they are. Then, the features are preprocessed and… More >

Pengpeng Zhi^1,2,3, Zhonglai Wang^1,2,*, Bingzhi Chen³, Ziqiang Sheng⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1001-1022, 2022, DOI:10.32604/cmes.2022.019835 - 14 March 2022

Abstract Although various types of anti-roll torsion bars have been developed to inhibit excessive roll angle of the electric multiple unit (EMU) car body, it is critical to ensure the reliability of structural design due to the complexity of the problems involving time and uncertainties. To address this issue, a multi-objective fuzzy design optimization model is constructed considering time-variant stiffness and strength reliability constraints for the anti-roll torsion bar. A hybrid optimization strategy combining the design of experiment (DoE) sampling and non-linear programming by quadratic lagrangian (NLPQL) is presented to deal with the design optimization model. More >

Dandan Xu¹, Haijian Shao^1,*, Xing Deng^1,2, Xia Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 567-597, 2022, DOI:10.32604/cmes.2022.019245 - 14 March 2022

Abstract As wind and photovoltaic energy become more prevalent, the optimization of power systems is becoming increasingly crucial. The current state of research in renewable generation and power forecasting technology, such as wind and photovoltaic power (PV), is described in this paper, with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting. The methods for forecasting wind power and PV production. The physical model, statistical learning method, and machine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production. More >

Yaning Xiao, Xue Sun^*, Yanling Guo, Sanping Li, Yapeng Zhang, Yangwei Wang

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 815-850, 2022, DOI:10.32604/cmes.2022.019198 - 14 March 2022

Abstract Gorilla troops optimizer (GTO) is a newly developed meta-heuristic algorithm, which is inspired by the collective lifestyle and social intelligence of gorillas. Similar to other metaheuristics, the convergence accuracy and stability of GTO will deteriorate when the optimization problems to be solved become more complex and flexible. To overcome these defects and achieve better performance, this paper proposes an improved gorilla troops optimizer (IGTO). First, Circle chaotic mapping is introduced to initialize the positions of gorillas, which facilitates the population diversity and establishes a good foundation for global search. Then, in order to avoid getting… More >

Shaoqiang Xu¹, Weiwei Li^1,*, Lin Li², Tao Li¹, Chicheng Ma¹

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 929-947, 2022, DOI:10.32604/cmes.2022.018964 - 14 March 2022

Abstract Thin-walled structures have been used in many fields due to their superior mechanical properties. In this paper, two types of hierarchical multi-cell tubes, inspired by the self-similarity of Pinus sylvestris, are proposed to enhance structural energy absorption performance. The finite element models of the hierarchical structures are established to validate the crashworthiness performance under axial dynamic load. The theoretical model of the mean crushing force is also derived based on the simplified super folded element theory. The finite element results demonstrate that the energy absorption characteristics and deformation mode of the bionic hierarchical thin-walled tubes More >

Sridharan Kannan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 677-694, 2022, DOI:10.32604/cmes.2022.018580 - 14 March 2022

Abstract With the worldwide analysis, heart disease is considered a significant threat and extensively increases the mortality rate. Thus, the investigators mitigate to predict the occurrence of heart disease in an earlier stage using the design of a better Clinical Decision Support System (CDSS). Generally, CDSS is used to predict the individuals’ heart disease and periodically update the condition of the patients. This research proposes a novel heart disease prediction system with CDSS composed of a clustering model for noise removal to predict and eliminate outliers. Here, the Synthetic Over-sampling prediction model is integrated with the… More >

Ali E. Takieldeen¹, El-Sayed M. El-kenawy^1,2, Mohammed Hadwan^3,4,5,*, Rokaia M. Zaki^6,7

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1465-1481, 2022, DOI:10.32604/cmc.2022.026026 - 24 February 2022

Abstract Dipper throated optimization (DTO) algorithm is a novel with a very efficient metaheuristic inspired by the dipper throated bird. DTO has its unique hunting technique by performing rapid bowing movements. To show the efficiency of the proposed algorithm, DTO is tested and compared to the algorithms of Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Genetic Algorithm (GA) based on the seven unimodal benchmark functions. Then, ANOVA and Wilcoxon rank-sum tests are performed to confirm the effectiveness of the DTO compared to other optimization techniques. Additionally, to demonstrate the proposed More >

Muhammad Irfan^1,*, Nasir Ayub², Faisal Althobiani³, Zain Ali⁴, Muhammad Idrees⁵, Saeed Ullah², Saifur Rahman¹, Abdullah Saeed Alwadie¹, Saleh Mohammed Ghonaim³, Hesham Abdushkour³, Fahad Salem Alkahtani¹, Samar Alqhtani⁶, Piotr Gas⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2141-2158, 2022, DOI:10.32604/cmc.2022.025466 - 24 February 2022

Abstract One of the major concerns for the utilities in the Smart Grid (SG) is electricity theft. With the implementation of smart meters, the frequency of energy usage and data collection from smart homes has increased, which makes it possible for advanced data analysis that was not previously possible. For this purpose, we have taken historical data of energy thieves and normal users. To avoid imbalance observation, biased estimates, we applied the interpolation method. Furthermore, the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further processing.… More >

Mutasem K. Alsmadi^1,*, Ghaith M. Jaradat², Malek Alzaqebah³, Ibrahim ALmarashdeh¹, Fahad A. Alghamdi¹, Rami Mustafa A. Mohammad⁴, Nahier Aldhafferi⁴, Abdullah Alqahtani⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1995-2014, 2022, DOI:10.32604/cmc.2022.025077 - 24 February 2022

Abstract Timetabling problem is among the most difficult operational tasks and is an important step in raising industrial productivity, capability, and capacity. Such tasks are usually tackled using metaheuristics techniques that provide an intelligent way of suggesting solutions or decision-making. Swarm intelligence techniques including Particle Swarm Optimization (PSO) have proved to be effective examples. Different recent experiments showed that the PSO algorithm is reliable for timetabling in many applications such as educational and personnel timetabling, machine scheduling, etc. However, having an optimal solution is extremely challenging but having a sub-optimal solution using heuristics or metaheuristics is… More >