Smarajit Ghosh^*

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 181-197, 2023, DOI:10.32604/iasc.2023.026496 - 06 June 2022

Abstract The primary purpose of the Energy Management Scheme (EMS) is to monitor the energy fluctuations present in the load profile. In this paper, the improved model predictive controller is adopted for the EMS in the power system. Emperor Penguin Optimization (EPO) algorithm optimized Artificial Neural Network (ANN) with Model Predictive Control (MPC) scheme for accurate prediction of load and power forecasting at the time of pre-optimizing EMS is presented. For the power generation, Renewable Energy Sources (RES) such as photo voltaic (PV) and wind turbine (WT) are utilized along with that the fuel cell is… More >

Polin Rahman¹, Ahmed Rifat¹, MD. IftehadAmjad Chy¹, Mohammad Monirujjaman Khan^1,*, Mehedi Masud², Sultan Aljahdali²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 757-775, 2023, DOI:10.32604/csse.2023.021469 - 01 June 2022

Abstract Heart failure is now widely spread throughout the world. Heart disease affects approximately 48% of the population. It is too expensive and also difficult to cure the disease. This research paper represents machine learning models to predict heart failure. The fundamental concept is to compare the correctness of various Machine Learning (ML) algorithms and boost algorithms to improve models’ accuracy for prediction. Some supervised algorithms like K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Trees (DT), Random Forest (RF), Logistic Regression (LR) are considered to achieve the best results. Some boosting algorithms like Extreme Gradient… More >

Chao-Hsi Huang¹, Tsung-Shun Hsieh^2,3, Hsiao-Ting Chien⁴, Ehsan Eftekhari-Zadeh^5,*, Saba Amiri⁶

International Journal of Mental Health Promotion, Vol.24, No.6, pp. 825-841, 2022, DOI:10.32604/ijmhp.2022.021899 - 28 September 2022

Abstract In addition to the effect that the COVID-19 pandemic has had on the physical and mental health of individuals, it has also led to a change in the mental and emotional state of many employees. Especially among businesses and private companies, which faced many restrictions due to the special conditions of the pandemic. Therefore, the present study aimed to design an artificial neural network with MLP technique to analyze the relationship between demographic variables, resilience, COVID-19 and burnout in start-ups in Iran. The research method was quantitative. Managers and employees of start-ups formed the statistical… More >

Wajaree Weera¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Sakda Noinang⁴, Thongchai Botmart^1,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4833-4849, 2022, DOI:10.32604/cmc.2022.030888 - 28 July 2022

Abstract The purpose of this research is to construct an integrated neuro swarming scheme using the procedures of the artificial neural networks (ANNs) with the use of global search particle swarm optimization (PSO) along with the competent local search interior-point programming (IPP) called as ANN-PSOIPP. The proposed computational scheme is implemented for the numerical simulations of the third order nonlinear delay differential Emden-Fowler model (TON-DD-EFM). The TON-DD-EFM is based on two types along with the particulars of shape factor, delayed terms, and singular points. A merit function is performed using the optimization of PSOIPP to find More >

K. Santosh Jhansi^1,2,*, P. Ravi Kiran Varma², Sujata Chakravarty³

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6327-6345, 2022, DOI:10.32604/cmc.2022.030878 - 28 July 2022

Abstract Malware Security Intelligence constitutes the analysis of applications and their associated metadata for possible security threats. Application Programming Interfaces (API) calls contain valuable information that can help with malware identification. The malware analysis with reduced feature space helps for the efficient identification of malware. The goal of this research is to find the most informative features of API calls to improve the android malware detection accuracy. Three swarm optimization methods, viz., Ant Lion Optimization (ALO), Cuckoo Search Optimization (CSO), and Firefly Optimization (FO) are applied to API calls using auto-encoders for identification of most influential More >

Sakda Noinang¹, Zulqurnain Sabir², Gilder Cieza Altamirano³, Muhammad Asif Zahoor Raja⁴, Manuel Jesús Sànchez-Chero⁵, María-Verónica Seminario-Morales⁵, Wajaree Weera^6,*, Thongchai Botmart⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4851-4868, 2022, DOI:10.32604/cmc.2022.029437 - 28 July 2022

Abstract The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible individuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using More >

Mir Mushhood Afsar¹, Shizza Saqib¹, Yazeed Yasin Ghadi², Suliman A. Alsuhibany³, Ahmad Jalal¹, Jeongmin Park^4,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4763-4777, 2022, DOI:10.32604/cmc.2022.028618 - 28 July 2022

Abstract Virtual reality is an emerging field in the whole world. The problem faced by people today is that they are more indulged in indoor technology rather than outdoor activities. Hence, the proposed system introduces a fitness solution connecting virtual reality with a gaming interface so that an individual can play first-person games. The system proposed in this paper is an efficient and cost-effective solution that can entertain people along with playing outdoor games such as badminton and cricket while sitting in the room. To track the human movement, sensors Micro Processor Unit (MPU6050) are used… More >

G. Naveen Sundar¹, Stalin Selvaraj², D. Narmadha¹, K. Martin Sagayam³, A. Amir Anton Jone³, Ayman A. Aly⁴, Dac-Nhuong Le^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 31-46, 2022, DOI:10.32604/cmes.2022.019914 - 18 July 2022

Abstract Hepatocellular carcinoma (HCC) is one major cause of cancer-related mortality around the world. However, at advanced stages of HCC, systematic treatment options are currently limited. As a result, new pharmacological targets must be discovered regularly, and then tailored medicines against HCC must be developed. In this research, we used biomarkers of HCC to collect the protein interaction network related to HCC. Initially, DC (Degree Centrality) was employed to assess the importance of each protein. Then an improved Graph Coloring algorithm was used to rank the target proteins according to the interaction with the primary target More >

Majida Kazmi^1,*, Hashim Raza Khan^1,2, Lubaba², Mohammad Hashir Bin Khalid², Saad Ahmed Qazi^1,2

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2351-2370, 2022, DOI:10.32604/cmc.2022.026265 - 16 June 2022

Abstract Energy management benefits both consumers and utility companies alike. Utility companies remain interested in identifying and reducing energy waste and theft, whereas consumers’ interest remain in lowering their energy expenses. A large supply-demand gap of over 6 GW exists in Pakistan as reported in 2018. Reducing this gap from the supply side is an expensive and complex task. However, efficient energy management and distribution on demand side has potential to reduce this gap economically. Electricity load forecasting models are increasingly used by energy managers in taking real-time tactical decisions to ensure efficient use of resources.… More >

Rania Jradi^1,*, Christophe Marvillet², Mohamed-Razak Jeday¹

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.5, pp. 1511-1519, 2022, DOI:10.32604/fdmp.2022.021925 - 27 May 2022

Abstract The accumulation of undesirable deposits on the heat exchange surface represents a critical issue in industrial heat exchangers. Taking experimental measurements of the fouling is relatively difficult and, often, this method does not lead to precise results. To overcome these problems, in the present study, a new approach based on an Artificial Neural Network (ANN) is used to predict the fouling resistance as a function of specific measurable variables in the phosphoric acid concentration process. These include: the phosphoric acid inlet and outlet temperatures, the steam temperature, the phosphoric acid density, the phosphoric acid volume… More >