A feature selection approach based on NSGA-II with ReliefF

Xue, Yu; Zhu, Haokai; Neri, Ferrante

doi:10.1016/j.asoc.2023.109987

Cited by 27 publications

(12 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this crossover, only one offspring was produced and characterized as the convex linear combination of the parents, and gene positioning was chosen at random by exchanging the positions of their respective genes. Following that, various types of real coded crossover operators [29], [30], [31], [32], [33], [34] were developed to achieve faster convergence as well as greater accuracy and efficiency. We develop a novel real-coded crossover operator for this purpose.…”

Section: Literature Reviewmentioning

confidence: 99%

Installation of Smog-Free Towers Using Novel Real Coded Genetic Algorithm

Kumar,

Deep,

Nagar

2024

IEEE Access

View full text Add to dashboard Cite

The circle packing problem involves finding the best way to place non-overlapping circles within a given space, while the smog-free tower installation problem aims to minimize the exposure of residents to secondhand smog by identifying the optimal tower locations. This study proposes a Real Coded Genetic Algorithm (RCGA) that uses real-valued representations of circle positions to solve the smog-free tower installation problem. A new crossover operator is introduced, combining the information from two parent solutions to generate two new offspring solutions. The operator uses a random crossover point and two scaling factors to control the amount of information exchanged. The performance of the operator is evaluated on CEC-2017 benchmark problem set and compared to other commonly used operators, with results indicating that it produces high-quality solutions and outperforms other operators in terms of solution quality and convergence speed. This research contributes to developing effective optimization algorithms that can have important implications for improving public health and reducing the negative effects of secondhand smog.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Installation of Smog-Free Towers Using Novel Real Coded Genetic Algorithm

Kumar,

Deep,

Nagar

2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The Relief-F algorithm, a classic multivariate filtering feature selection method used in various classification problems, assigns weights to features based on their relevance to the landform class. Features weighing less than a specified threshold are rejected [31]. The algorithm is computed as follows: given class labels, there are l classes C = [C 1 , C 2 ,.…”

Section: Importance Ranking Of Featuresmentioning

confidence: 99%

Detailed Land Use Classification in a Rare Earth Mining Area Using Hyperspectral Remote Sensing Data for Sustainable Agricultural Development

Li,

Zhou

et al. 2024

Sustainability

View full text Add to dashboard Cite

In China, ion-adsorbing rare earth minerals are mainly located in the southern hilly areas and are important strategic resources. Extensive long-term mining has severely damaged the land cover in mining areas, caused soil pollution and terrain fragmentation, disrupted the balance between mining and agriculture, severely restricted agricultural development, and affected ecological development. Precise and detailed classification of land use within mining areas is crucial for monitoring the sustainable development of agricultural ecology in these areas. In this study, we leverage the high spatial and high spectral resolution characteristics of the Zhuhai-1 (OHS) hyperspectral image datasets. We create four types of datasets based on spectral, vegetation, red edge, and texture characteristics. These datasets are optimized for multifaceted features, considering the complex land use scenario in rare earth mining areas. Additionally, we design seven optimal combination schemes for features. This is performed to examine the impact of different schemes on land use classification in rare earth mining areas and the accuracy of identifying agricultural land classes from broken blocks. The results show that (1) the inclusion of texture features has the most obvious effect on the overall classification accuracy; (2) the red edge feature has the worst effect on improving the overall accuracy of the surface classification; however, it has a prominent effect on the identification of agricultural lands such as farmland, orchards, and reclaimed vegetation; and (3), following the combination of various optimization features, the land use classification yielded the highest overall accuracy, at 88.16%. Furthermore, the comprehensive identification of various agricultural land classes, including farmland, orchards, and greenhouse vegetables, yielded the most desirable outcomes. The research results not only highlight the advantages of hyperspectral images for complex terrain classification and recognition but also address the previous limitations in the application of hyperspectral datasets over wide mining areas. Additionally, the results underscore the reliability of feature selection methods in reducing information redundancy and improving classification accuracy. The proposed feature selection combination, based on OHS hyperspectral datasets, offers technical support and guidance for the detailed classification of complex land use in mining areas and the accurate monitoring of agroecological environments.

show abstract

“…For instance, hybrid heuristics, which combine the strengths of different optimization strategies, have shown remarkable success in online learning environments, optimizing learning paths and content delivery [71]. Similarly, in the realm of scheduling and multi-objective optimization, metaheuristics have provided flexible and robust solutions, adeptly balancing conflicting objectives [72,73].…”

Section: Exploring Advanced Optimization Algorithmsmentioning

confidence: 99%