G. Geethamahalakshmi^1,*, N. Kalaiarasi², D. Nageswari¹

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1667-1685, 2022, DOI:10.32604/iasc.2022.022728 - 09 December 2021

Abstract Solar energy is the radiant heat and light energy harvested by ultra violet rays to convert into electrical Direct Current (DC). The solar energy stood ahead of other renewable energy as it can produce a constant level of alternating current over the year with minimal harmonic distortions. The renewable energy attracts the energy harvesters as there is rise of deficiency of carbon and reduction of efficiency in thermal energy generation. The concerns associated with the solar power generation are the fluctuation in the generated direct current due to the displacement of sun and deviation in… More >

Mohd Anul Haq^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2363-2381, 2022, DOI:10.32604/cmc.2022.023059 - 07 December 2021

Abstract Water received in rainfall is a crucial natural resource for agriculture, the hydrological cycle, and municipal purposes. The changing rainfall pattern is an essential aspect of assessing the impact of climate change on water resources planning and management. Climate change affected the entire world, specifically India’s fragile Himalayan mountain region, which has high significance due to being a climatic indicator. The water coming from Himalayan rivers is essential for 1.4 billion people living downstream. Earlier studies either modeled temperature or rainfall for the Himalayan area; however, the combined influence of both in a long-term analysis More >

Saima Hassan¹, Mojtaba Ahmadieh Khanesar², Nazar Kalaf Hussein³, Samir Brahim Belhaouari^4,*, Usman Amjad⁵, Wali Khan Mashwani⁶

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3513-3531, 2022, DOI:10.32604/cmc.2022.022018 - 07 December 2021

Abstract The estimation of the fuzzy membership function parameters for interval type 2 fuzzy logic system (IT2-FLS) is a challenging task in the presence of uncertainty and imprecision. Grasshopper optimization algorithm (GOA) is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature, which has good convergence ability towards optima. The main objective of this paper is to apply GOA to estimate the optimal parameters of the Gaussian membership function in an IT2-FLS. The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers… More >

Hatim G. Zaini^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2303-2314, 2022, DOI:10.32604/cmc.2022.021998 - 07 December 2021

Abstract This paper gives and analyses data-driven prediction models for the energy usage of appliances. Data utilized include readings of temperature and humidity sensors from a wireless network. The building envelope is meant to minimize energy demand or the energy required to power the house independent of the appliance and mechanical system efficiency. Approximating a mapping function between the input variables and the continuous output variable is the work of regression. The paper discusses the forecasting framework FOPF (Feature Optimization Prediction Framework), which includes feature selection optimization: by removing non-predictive parameters to choose the best-selected feature More >

Muhammad Zulqarnain¹, Rozaida Ghazali^1,*, Habib Shah², Lokman Hakim Ismail¹, Abdullah Alsheddy³, Maqsood Mahmud⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3051-3068, 2022, DOI:10.32604/cmc.2022.021629 - 07 December 2021

Abstract Air pollution is a significant problem in modern societies since it has a serious impact on human health and the environment. Particulate Matter (PM_2.5) is a type of air pollution that contains of interrupted elements with a diameter less than or equal to 2.5 m. For risk assessment and epidemiological investigations, a better knowledge of the spatiotemporal variation of PM_2.5 concentration in a constant space-time area is essential. Conventional spatiotemporal interpolation approaches commonly relying on robust presumption by limiting interpolation algorithms to those with explicit and basic mathematical expression, ignoring a plethora of hidden but crucial… More >

Malini M. Patil^1,*, P. M. Rekha¹, Arun Solanki², Anand Nayyar^3,4, Basit Qureshi⁵

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2347-2361, 2022, DOI:10.32604/cmc.2022.021447 - 07 December 2021

Abstract In the past few decades, climatic changes led by environmental pollution, the emittance of greenhouse gases, and the emergence of brown energy utilization have led to global warming. Global warming increases the Earth's temperature, thereby causing severe effects on human and environmental conditions and threatening the livelihoods of millions of people. Global warming issues are the increase in global temperatures that lead to heat strokes and high-temperature-related diseases during the summer, causing the untimely death of thousands of people. To forecast weather conditions, researchers have utilized machine learning algorithms, such as autoregressive integrated moving average,… More >

Qian Wang¹, Xiaolong Yang^2,*, Di Pu³, Yingying Fan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 269-286, 2022, DOI:10.32604/cmes.2022.016437 - 29 November 2021

Abstract This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine (DRBM) optimized by the Lion algorithm (LA). Firstly, two factors including transmission and distribution price reform (TDPR) and 5G station construction were comprehensively incorporated into the consideration of influencing factors, and the fuzzy threshold method was used to screen out critical influencing factors. Then, the LA was used to optimize the parameters of the DRBM model to improve the model's prediction accuracy, and the model was trained with the selected influencing factors and investment. Finally, the LA-DRBM model… More >

Ming Zhang, Hongbo Li, Xing Deng^*

Energy Engineering, Vol.119, No.1, pp. 237-252, 2022, DOI:10.32604/EE.2022.017916 - 22 November 2021

Abstract The inherent randomness, intermittence and volatility of wind power generation compromise the quality of the wind power system, resulting in uncertainty in the system's optimal scheduling. As a result, it's critical to improve power quality and assure real-time power grid scheduling and grid-connected wind farm operation. Inferred statistics are utilized in this research to infer general features based on the selected information, confirming that there are differences between two forecasting categories: Forecast Category 1 (0–11 h ahead) and Forecast Category 2 (12–23 h ahead). In z-tests, the null hypothesis provides the corresponding quantitative findings. To More >

N. Ashwini^1,*, V. Nagaveni², Manoj Kumar Singh³

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 893-908, 2022, DOI:10.32604/iasc.2022.022231 - 17 November 2021

Abstract Forecasting for a time series signal carrying single pattern characteristics can be done properly using function mapping-based principle by a well-designed artificial neural network model. But the performances degraded very much when time series carried the mixture of different patterns characteristics. The level of difficulty increases further when there is a need to predict far time samples. Among several possible mixtures of patterns, the trend-cycle time series is having its importance because of its occurrence in many real-life applications like in electric power generation, fuel consumption and automobile sales. Over the mixed characteristics of patterns,… More >

Jabeen Sultana^1,*, Anjani Kumar Singha², Shams Tabrez Siddiqui³, Guthikonda Nagalaxmi⁴, Anil Kumar Sriram⁵, Nitish Pathak⁶

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1007-1024, 2022, DOI:10.32604/iasc.2022.021507 - 17 November 2021

Abstract COVID-19 is a novel virus that spreads in multiple chains from one person to the next. When a person is infected with this virus, they experience respiratory problems as well as rise in body temperature. Heavy breathlessness is the most severe sign of this COVID-19, which can lead to serious illness in some people. However, not everyone who has been infected with this virus will experience the same symptoms. Some people develop cold and cough, while others suffer from severe headaches and fatigue. This virus freezes the entire world as each country is fighting against… More >