Mame Cheikh Diouf¹, Mactar Faye^1,2,*, Ababacar Thiam^1,2, Alphousseyni Ndiaye^1,2, Vincent Sambou²

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.5, pp. 1275-1284, 2022, DOI:10.32604/fdmp.2022.021972

Abstract The operating temperature is a critical factor affecting the performances of photovoltaic (PV) modules. In this work, relevant models are proposed for the prediction of this operating temperature using data (ambient temperature and solar irradiance) based on real measurements conducted in the tropical region. For each weather condition (categorized according to irradiance and temperature levels), the temperatures of the PV modules obtained using the proposed approach is compared with the corresponding experimentally measured value. The results show that the proposed models have a smaller Root Mean Squared Error than other models developed in the literature for all weather conditions, which… More >

Mesfer Al Duhayyim¹, Amani Abdulrahman Albraikan², Fahd N. Al-Wesabi^3,4, Hiba M. Burbur⁵, Mohammad Alamgeer⁶, Anwer Mustafa Hilal⁷, Manar Ahmed Hamza^7,*, Mohammed Rizwanullah⁷

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3953-3968, 2022, DOI:10.32604/cmc.2022.022692

Abstract Short-term traffic flow prediction (TFP) is an important area in intelligent transportation system (ITS), which is used to reduce traffic congestion. But the avail of traffic flow data with temporal features and periodic features are susceptible to weather conditions, making TFP a challenging issue. TFP process are significantly influenced by several factors like accident and weather. Particularly, the inclement weather conditions may have an extreme impact on travel time and traffic flow. Since most of the existing TFP techniques do not consider the impact of weather conditions on the TF, it is needed to develop effective TFP with the consideration… More >

Ghulfam Zahra¹, Muhammad Imran¹, Abdulrahman M. Qahtani^2,*, Abdulmajeed Alsufyani², Omar Almutiry³, Awais Mahmood³, Fayez Eid Alazemi⁴

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3465-3481, 2021, DOI:10.32604/cmc.2021.017454

Abstract In recent years, video surveillance application played a significant role in our daily lives. Images taken during foggy and haze weather conditions for video surveillance application lose their authenticity and hence reduces the visibility. The reason behind visibility enhancement of foggy and haze images is to help numerous computer and machine vision applications such as satellite imagery, object detection, target killing, and surveillance. To remove fog and enhance visibility, a number of visibility enhancement algorithms and methods have been proposed in the past. However, these techniques suffer from several limitations that place strong obstacles to the real world outdoor computer… More >