Intelligent optimization framework of near zero energy consumption building performance based on a hybrid machine learning algorithm
The realization of a near zero energy consumption building (NZEB) is one of the important
goals to promote the sustainable development of green buildings. To achieve the goal of …
goals to promote the sustainable development of green buildings. To achieve the goal of …
An easy-to-use real-world multi-objective optimization problem suite
Although synthetic test problems are widely used for the performance assessment of
evolutionary multi-objective optimization algorithms, they are likely to include unrealistic …
evolutionary multi-objective optimization algorithms, they are likely to include unrealistic …
Determining importance of many-objective optimisation competitive algorithms evaluation criteria based on a novel fuzzy-weighted zero-inconsistency method
Along with the developments of numerous MaOO algorithms in the last decades, comparing
the performance of MaOO algorithms with one another is also highly needed. Many studies …
the performance of MaOO algorithms with one another is also highly needed. Many studies …
PCA-ANN integrated NSGA-III framework for dormitory building design optimization: Energy efficiency, daylight, and thermal comfort
Abstract “Framework” and “case-study” are the two most prominent features in the
optimization of architectural building design. The first can improve the speed of the process …
optimization of architectural building design. The first can improve the speed of the process …
Hybrid classifier ensemble for imbalanced data
The class imbalance problem has become a leading challenge. Although conventional
imbalance learning methods are proposed to tackle this problem, they have some …
imbalance learning methods are proposed to tackle this problem, they have some …
Review of the research landscape of multi-criteria evaluation and benchmarking processes for many-objective optimization methods: coherent taxonomy, challenges …
Evaluation and benchmarking of many-objective optimization (MaOO) methods are
complicated. The rapid development of new optimization algorithms for solving problems …
complicated. The rapid development of new optimization algorithms for solving problems …
Simulation-based passenger evacuation optimization in metro stations considering multi-objectives
K Guo, L Zhang - Automation in Construction, 2022 - Elsevier
Evacuation is critical for safety management due to the highly overcrowded passengers in
the metro stations. A simulation-based approach integrating Random Forest (RF) and Non …
the metro stations. A simulation-based approach integrating Random Forest (RF) and Non …
An integrated framework with evolutionary algorithm for multi-scenario multi-objective optimization problems
Multi-objective optimization problems often load in the multi-scenario environment, and they
can be modeled as multi-scenario multi-objective optimization problems (MSMOs). So far …
can be modeled as multi-scenario multi-objective optimization problems (MSMOs). So far …
Optimal walker constellation design of LEO-based global navigation and augmentation system
M Guan, T Xu, F Gao, W Nie, H Yang - Remote Sensing, 2020 - mdpi.com
Low Earth orbit (LEO) satellites located at altitudes of 500 km~ 1500 km can carry much
stronger signals and move faster than medium Earth orbit (MEO) satellites at about a 20,000 …
stronger signals and move faster than medium Earth orbit (MEO) satellites at about a 20,000 …
Two-stage storage assignment to minimize travel time and congestion for warehouse order picking operations
This research presents a systematic and integrated approach that extends the correlated
storage assignment strategy to improve the efficiency of warehouse order picking …
storage assignment strategy to improve the efficiency of warehouse order picking …