A novelty mode decomposition method and its application in dynamic characteristic identification of bridge GNSS monitoring data. [PDF]
Wang X, Luo L, Liu J.
europepmc +1 more source
Multi-Objective Task Scheduling for Vehicle-UAV Synchronous Cooperative Distribution Network Inspection. [PDF]
Liu X +5 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
NeuroAction: a neuroevolutionary approach to reinforcement learning for autonomous vehicles. [PDF]
Aboyeji E +3 more
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
Optimized scheduling of integrated energy systems: a multi-dimensional electricity, hydrogen, ammonia, heat synergy approach using the LSDBO-WOA algorithm. [PDF]
Tu N, Yang J, Yan X, Fan Z.
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
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
Adaptive Policy Switching for Multi-Agent ASVs in Multi-Objective Aquatic Cleaning Environments. [PDF]
Seck D +4 more
europepmc +1 more source
Neural Network Repair With Shapley‐Guided Search
ABSTRACT The deployment of deep neural networks (DNNs) in safety‐critical domains is critically hampered by their vulnerability to defects, which can arise from malicious attacks or low‐quality data. Therefore, precisely locating the network components responsible for these defects, and subsequently repairing them without compromising overall model ...
Xiaofu Du +4 more
wiley +1 more source

