Santiago Bañales^1,2,*, Raquel Dormido¹, Natividad Duro¹

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 869-907, 2025, DOI:10.32604/cmes.2024.054946 - 17 December 2024

Abstract Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’ participation in the energy transition. This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons. Smart meter data is split between daily and hourly normalized time series to assess monthly, weekly, daily, and hourly seasonality patterns separately. The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series… More > Graphic Abstract

Faisal Bahadur^1,*, Arif Iqbal Umar¹, Insaf Ullah², Fahad Algarni³, Muhammad Asghar Khan², Samih M. Mostafa⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1483-1493, 2022, DOI:10.32604/cmc.2022.024936 - 24 February 2022

Abstract Scalability is one of the utmost nonfunctional requirement of server applications, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) has been used extensively as a middleware service in server applications. The size of thread pool is the most significant factor, that affects the overall performance of servers. Determining the optimal size of thread pool dynamically on runtime is a challenging problem. The most widely used and simple method to tackle this problem is to keep the size of thread… More >