A fast optimized algorithm based on the NSGA — II for microwave windows

Gong, Jinjie; Zhu, Xiao; Hu, Quan; Hu, Yulu; Bin, Li

doi:10.1109/ivec.2017.8289508

Cited by 7 publications

(2 citation statements)

References 2 publications

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“…For multi-objective optimal problems, many scholars are committed to relevant research and build many superior algorithms, of which NSGA-II is the most common one [39]. As well known, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is one of the most popular optimization algorithms, which has not only the ability of optimizing multiple goals with several decision variables and constraint conditions simultaneously but also the ability of finding global optimum solutions [40]. However, it cannot deal with the multi-objective collaborative optimization for multidiscipline intersection well, such as the expert system and probability statistics proposed in this study.…”

Section: Hierarchical Multi-objective Optimization Algorithmmentioning

confidence: 99%

A Novel Fault Identification Method Driven by Knowledge and Data

Wan

Zhang

2022

IEEE Access

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In the field of intelligent manufacturing, fault identification is an effective way to improve product service by identifying the cause of failures. For addressing it, the Generalized Bayesian Network (GBN) model is extended based on the traditional Bayesian Network in this paper, which redefines the directed edges and probability parameters among nodes. Compared with Bayesian Network, the GBN model has the ability to simultaneously define causality and correlation of variables. In addition, the structure of network is not only based on statistical data but also driven by expert knowledge. In order to achieve the collaboration of data and knowledge while maintaining the consistency, a hierarchical collaborative framework is designed including the data layer and knowledge layer. Furthermore, a hierarchical multi-objective optimization algorithm, namely Hierarchical Non-dominated Sorting Genetic Algorithm II (HNSGA-II), is advanced to solve the proposed model. Finally, an industrial case study for fault cause identification targeting the product service helps illustrate all details.INDEX TERMS Fault identification, generalized bayesian network (GBN), data and knowledge, hierarchical collaborative framework, hierarchical non-dominated sorting genetic algorithm II (HNSGA-II).

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Section: Hierarchical Multi-objective Optimization Algorithmmentioning

confidence: 99%

A Novel Fault Identification Method Driven by Knowledge and Data

Wan

Zhang

2022

IEEE Access

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“…In the dissertation, the nondominated sorting genetic algorithm (NSGA II) 38 was adopted for the multi-objective optimization due to its low computation cost. [39][40][41] This balance of objective functions is achieved by adding traditional GA operations to two new processes, the nondominated sorting and the crowding distance assignment. The nondominated sorting sorts the solutions by assigning a dominating rank to all solutions.…”

Section: Multiple Objectives Genetic Algorithmmentioning

confidence: 99%

Unpaved road detection using optimized log Gabor filter banks

Plodpradista¹

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The revised unpaved road detection system (RURD) is a novel method for detecting unpaved roads in an arid environment from color imagery collected by a forward-looking camera mounted on a moving platform. The objective is to develop and validate a novel system with the ability to detect an unpaved road at a look-ahead distance up to 40 meters that does not utilize an expensive sensor, i.e., LIDAR but instead a low-cost color camera sensor. The RURD system is composed of two stages, the road region estimation (RRE) and the road model formation (RMF). The RRE stage classifies the image patches selected at 20-meter distance from the camera and labels them to either road or non-road. The classification result is used as a high confidence road area in the image, which is used in the RMF stage. The RMF stage uses log Gabor filter bank to extract road pixels that connect to the high confidence road region and generates a 3rd degree polynomial curve to represent the road model in a given image. The road model allows the system to extend the detection range from 20 meters to farther look-ahead distance. The RURD system is evaluated with two-years worth of data collection that measures both spatial and temporal precisions. The system is also benchmarked against an algorithm from Rasmussen entitled "Grouping Dominant Orientations for Ill-Structured Roads Following", which shown an average increase detection accuracy over 30 [percent].

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Elite-guided multi-objective cuckoo search algorithm based on crossover operation and information enhancement

Yang

Hao²,

Yang³

et al. 2022

Soft Comput

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In recent years, the cuckoo search (CS) algorithm has been successfully applied to single-objective optimization problems. But in real life, most optimization problems are multi-objective optimization problems(MOPs). In order to enable CS to better solve MOPs, this paper proposes an elite-guided multi-objective cuckoo search algorithm based on cross-operation and information enhancement (CIE-MOCS). This algorithm first enhances its population diversity through crossover operation, then adds elite individuals to guide its update process to speed up the algorithm convergence speed. Finally, the method of information enhancement is adopted in the abandonment process, so that the algorithm is not easy to fall into the local optimum. In order to verify the performance of the algorithm, this paper uses a variety of benchmark functions and performance evaluation indicators to evaluate it, and provides a case to verify the effectiveness of the algorithm in practical applications. The experimental resultsshow that CIE-MOCS has good performance compared with the contrasting algorithms.

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A fast optimized algorithm based on the NSGA — II for microwave windows

Cited by 7 publications

References 2 publications

A Novel Fault Identification Method Driven by Knowledge and Data

A Novel Fault Identification Method Driven by Knowledge and Data

Unpaved road detection using optimized log Gabor filter banks

Elite-guided multi-objective cuckoo search algorithm based on crossover operation and information enhancement

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