The roll of consumption energy forecasting is very important to make planning time-horizon strategy, and mitigate a great management. As result, improving the sustainability energy, creating clean environment. Aiming develop in different time horizons, this work gives results new hybrid method, which combine deep echo state network (DeepESN), with Binary genetic algorithm (BGA). DeepESN an exte...

This paper presents a Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) for the optimal operation of a complex multipurpose and multi-reservoir system. Firstly, MOEA/D decomposes a multi-objective optimization problem into a number of scalar optimization sub-problems and optimizes them simultaneously. It uses information of its several neighboring sub-problems for optimizin...

in recent years, significant research efforts have been devoted to the optimal planning of power systems. substation expansion planning (sep) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders to meet the future demand. the large number of design variables, and combination of discrete ...

In order to improve network throughput and reduce energy consumption, we propose in this paper a cross-layer optimization design that is able to achieve multicast utility maximization and energy consumption minimization. The joint optimization of congestion control and power allocation is formulated to be a nonlinear nonconvex problem. Using dual decomposition, a distributed optimization algori...

 This paper presents an optimal budget distribution method for low power circuit design using transistor sizing. The algorithm distributes the available budget on the transistors optimally by an efficient traversal of the Series Parallel Graph representations of functional units. The technique can be efficiently applied at different abstraction levels of the design as well as toward other opti...

A new optimization framework to maximize the performance and efficiency of morphable many-core accelerators is proposed. The devised methodology supports the co-existence of multiple optimization goals and constraints (e.g., computational performance, power, energy consumption and runtime reconfiguration overhead) by relying on a design space exploration approach based on a convenient adaptatio...