Most countries, including Japan, are focused on achieving net‐zero greenhouse gas (GHG) emissions by 2050, which requires quick action. Despite the increasing level of renewable power generation in power grids, fossil fuel power plants still have a significant role in producing GHG emissions, causing serious environmental issues.
Kadyrbek Kozhobekov +4 more
wiley +1 more source
GCAD: A Computational Framework for Mammalian Genetic Program Computer-Aided Design. [PDF]
Dreyer KS +9 more
europepmc +1 more source
A stochastic framework to assess the optimal allocation of limited vaccine doses in foot-and-mouth disease outbreaks using game theory. [PDF]
Moreno-Torres KI +6 more
europepmc +1 more source
Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation
Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou +4 more
wiley +1 more source
A multi dataset validation model for hybrid feature selection in wind energy maximum power point tracking systems. [PDF]
Duraisamy S, Thangavelu V.
europepmc +1 more source
Abstract In a multi‐row facility layout problem (MRFLP), facilities are arranged in more than one row under the limited layout area. Considering different layout factors, various extensions of MRFLP have been modelled. However, the orientation of input/output (I/O) point in a facility, as a key factor that plays a direct impact on flow cost, is seldom ...
Yinan Guo +5 more
wiley +1 more source
A Load-Balancing-Aware Learning Framework for Collaborative UAV-MEC Computation Offloading. [PDF]
Li H +7 more
europepmc +1 more source
Evolutionary Dynamic Multiobjective Optimisation Assisted by Inverse Regression Tree Predictor
ABSTRACT Dynamic multiobjective optimisation problems (DMOPs) are optimisation problems with multiple conflicting objectives that can change over time. Most dynamic multiobjective optimisation evolutionary algorithms (DMOEAs) attempt to estimate Pareto‐optimal sets (PS) directly in the decision space.
Kai Gao, Lihong Xu
wiley +1 more source
Improved many-objective particle swarm optimization based welding sequence optimization research. [PDF]
Dong L, Gu S, Dong J, Ji Q, Liu J.
europepmc +1 more source
A prescription-free, radiobiology-based framework for automated VMAT planning: A feasibility study in primary prostate cancer radiotherapy. [PDF]
Kuhn D +5 more
europepmc +1 more source

