Derivative-based band clustering and multi-agent PSO optimization for optimal band selection of hyper-spectral images

Kalidindi, Kishore Raju; Varma, G. P. S.; Davuluri, Rajyalakshmi

doi:10.1007/s11227-019-03058-3

Cited by 17 publications

(8 citation statements)

References 25 publications

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“…So the simulation experiment adopts ICAO's recommended value in the approach phase, and BV is 1 (NM) [34]. Collect the deviation values for analysis, and take the minimum deviation value to form the nominal velocity profile parameter according to the conservative principle [6]. Table 2 shows that the deviation of v4 is the smallest, then v4 is selected as the nominal velocity profile, and a schematic diagram of the nominal velocity profile established is as shown in Figure 7.…”

Section: Velocity Profile Designmentioning

confidence: 99%

“…In order to further improve the normal implementation of operational measures, the accurate, efficient, and fast aeronautical information is required to enable the intelligent operation of flight missions [4]. To this end, the ICAO proposed the concept of ASBU (Aviation System Block Upgrades) [5], while the United States advanced the NEXTGEN [6] and Europe came up with the 'Single European Sky Project' [7]. e composition of a new generation of aeronautical information structure has been promoted by a series of theoretical innovations and technological breakthroughs.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Multisource Dynamic Model in TBO

Xia

Yan

Zhang

2022

Mathematical Problems in Engineering

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When extracting flight data from airport terminal area, there are matters such as large volume, unclear features, and similar trend in time series. In order to deal with the related issues and to optimize the description, by combining with the TBO (Trajectory-Based Operation), an application proposed by the ICAO (International Civil Aviation Organization) in ASBU (Aviation System Block Upgrade), using multisource dynamic model to establish 4DDW (4D dynamic warping) algorithm, the multisource modeling integrated with evaluation system is proposed to realize the flight path optimization with time series characteristics and accord with the interval concept. The calculation results show that 4DDW can obtain the optimal solution for multiprofile calculation of TBO by comparing the composite trajectory deviation values and time dimension planning using the buffer and threshold values recommended by ICAO in airspace planning and flight procedure design. The results meet the requirements of high accuracy and convergence features of spatial waypoints and can improve the airport operation standards and terminal area capacity.

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Section: Velocity Profile Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Multisource Dynamic Model in TBO

Xia

Yan

Zhang

2022

Mathematical Problems in Engineering

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“…[−100, 100] 50 (0, 0, …, 0) 50 0 agents (MAPSO) [52] and differential evolution PSO (DEPSO) [53] have improved the performance of traditional PSO. Therefore, SRPSO, ALCPSO, APSO-SLC, HMPSO, IWPSO, CFPSO, DNPSO, CLPSO-LOT, SAPSO, MAPSO, and DEPSO will be compared with TCPSO to verify the performance of the proposed algorithm.…”

Section: Test Function Search Range Dimension Optimal Solutionmentioning

confidence: 99%

Team Collaboration Particle Swarm Optimization and Its Application on Reliability Optimization

Zheng¹,

Ma²,

Zhang³

et al. 2021

IJCIS

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Particle swarm optimization (PSO) tends to be premature convergence due to easily trapping into local suboptimal areas. In order to overcome the PSO's defects, the reasons causing the defects are analyzed and summarized as population diversity deficiency, insufficient information sharing, unbalance of exploitation and exploration, and single update strategy. On this basis, inspired by human team collaboration behavior, a team collaboration particle swarm optimization (TCPSO) is proposed. Diversified updates strategies, dynamic grouping strategy, selectivity vector, and decreasing and increasing inertia weight are designed in TCPSO to solve the defects' reasons and improve the optimization performance. Eight typical test functions have been used to evaluate and compare the performance of different PSO variants, and the results have been proven that the optimal results found by TCPSO are better compared with other PSO variants, which demonstrates the rationality and effectiveness of TCPSO. Finally, a real-world problem for reliability optimization are solved by five algorithms, and the results prove the convergence rate and stable optimization performance of TCPSO, TCPSO can provide better support for reliability optimization of complex system.

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“…The follow PSO variants were improved based on different strategies, so they were used for the comparison discussed in this paper. PSO variants include SRPSO (selfregulating PSO) [12], ALCPSO (aging leader and challengers PSO) [13], SLPSO (social learning PSO) [14], IWPSO (inertia weights PSO) [11], SFPSO (shrinkage factor PSO) [15], DNPSO (dynamic neighborhood PSO) [16], SAPSO (simulated annealing PSO) [17], and MAPSO (multiple agents PSO) [18]. Furthermore, the population size was 60, and the total iteration number was 400, and all the algorithms were operated in the same computational environment.…”

Section: Pso Performance Verificationmentioning

confidence: 99%

Intelligent Prediction of Aeroengine Wear Based on the SVR Optimized by GMPSO

Zheng

Gao

et al. 2021

Applied Sciences

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In order to predict aeroengine wear accurately and automatically, as a predictor, support vector regression (SVR) was optimized by means of particle swarm optimization (PSO). The guided mutation strategy of PSO (GMPSO) is presented herein to determine the proper structure parameters of an SVR, as well as the embedding dimensions of the training samples. The guided mutation strategy was able to increase the diversity of particles and improve the probability of finding the global extremum. Furthermore, single-step and multi-step prediction methods were designed to meet different accuracy requirements. A prediction comparison study on spectral analysis data was carried out, and the contrast experiments show that compared with SVR optimized by means of a traditional PSO, a neural network and an auto regressive moving average (ARMA) prediction model, the SVR optimized by means of the GMPSO approach produced prediction results not only with higher accuracy, but also with better consistency.

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Derivative-based band clustering and multi-agent PSO optimization for optimal band selection of hyper-spectral images

Cited by 17 publications

References 25 publications

Optimization of Multisource Dynamic Model in TBO

Optimization of Multisource Dynamic Model in TBO

Team Collaboration Particle Swarm Optimization and Its Application on Reliability Optimization

Intelligent Prediction of Aeroengine Wear Based on the SVR Optimized by GMPSO

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