Adaptive Kaniadakis entropy thresholding segmentation algorithm based on particle swarm optimization

Lei, Bo; Fan, Jiulun

doi:10.1007/s00500-019-04351-2

Cited by 22 publications

(6 citation statements)

References 20 publications

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“…The experimental environment uses an Inter (R) Croe (TM) i7-10845hCPU, a PC with a main frequency of 2.3GHz and a memory of 16G, the operating system uses a 64-bit Windows11 system, and the programming language uses MATLAB R2020a. Using SSA, PSO, adaptive step-size PSO (APSO) [31], GSO, and improved adaptive step-size GSO (IASGSO) [32], these five algorithms are compared and analyzed. The five comparison algorithms and MSSA were tested on four groups of test functions.…”

Section: E Mssa Time Complexitymentioning

confidence: 99%

Research on Multistrategy Improved Evolutionary Sparrow Search Algorithm and its Application

et al. 2022

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To address the problem of the sparrow search algorithm (SSA) has poor global search ability, weak local development ability, and easily falls into the local optimal solution, a multi-strategy improved evolutionary sparrow search algorithm (MSSA) is proposed. The introduction of the tent chaotic map improves the diversity of the initialization population, accelerates algorithm convergence, and improves convergence accuracy. Endow sparrow finders with a random search ability to coordinate the balance between global search and local development. To discover dangerous sparrow individuals, the mutation evolution operation is completed, and a greedy strategy is combined to improve the processing ability of the algorithm for local optimal solutions and make full use of each sparrow individual. Six benchmark functions were used to comprehensively verify the feasibility of the proposed algorithm based on four aspects: optimization ability, robustness, convergence ability, and optimization trajectory. These results indicate that the proposed algorithm is superior. Finally, through the comparison and analysis of the parameter identification and control strategies of the two servo systems in practical application, on the one hand, the advantages of the proposed algorithm in practical engineering applications are illustrated. In addition, a fuzzy PID control strategy based on MSSA is proposed. By adding step, sinusoidal, triangular wave and disturbance signals, simulation experiments show that the control strategy can significantly improve the dynamic and steady performance of the servo system.

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Section: E Mssa Time Complexitymentioning

confidence: 99%

Research on Multistrategy Improved Evolutionary Sparrow Search Algorithm and its Application

et al. 2022

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“…For this reason, it has attracted the interest of many researchers over the last two decades who have studied its foundations and mathematical aspects [49][50][51][52][53][54][55][56][57][58], the underlying thermodynamics [59,60], and specific applications of the theory to various fields. A non-exhaustive list of applications includes those in quantum statistics [61][62][63][64], in quantum entanglement [65,66], in plasma physics [67][68][69][70][71][72][73], in nuclear fission [74][75][76][77], in astrophysics [78][79][80][81], in quantum gravity [82][83][84][85][86][87], in geomechanics [88,89], in genomics [90,91], in complex networks [92][93][94], in economy [95]…”

Section: A the κ-Deformed Exponential Functionmentioning

confidence: 99%

The κ-statistics approach to epidemiology

Kaniadakis

Baldi

Deisboeck

et al. 2020

Preprint

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A great variety of complex physical, natural and artificial systems are governed by statistical distributions, which often follow a standard exponential function in the bulk, while their tail obeys the Pareto power law. The recently introduced κ-statistics framework predicts distribution functions with this feature. A growing number of applications in different fields of investigation are beginning to prove the relevance and effectiveness of κ-statistics in fitting empirical data. In this paper, we use κ-statistics to formulate a statistical approach for epidemiological analysis. We validate the theoretical results by fitting the derived κ-Weibull distributions with data from the plague pandemic of 1417 in Florence as well as data from the COVID-19 pandemic in China over the entire cycle that concludes in April 16, 2020. As further validation of the proposed approach we present a more systematic analysis of COVID-19 data from countries such as Germany, Italy, Spain and United Kingdom, obtaining very good agreement between theoretical predictions and empirical observations. For these countries we also study the entire first cycle of the pandemic which extends until the end of July 2020. The fact that both the data of the Florence plague and those of the Covid-19 pandemic are successfully described by the same theoretical model, even though the two events are caused by different diseases and they are separated by more than 600 years, is evidence that the κ-Weibull model has universal features.

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Section: A the κ-Deformed Exponential Functionmentioning

confidence: 99%

The κ-statistics approach to epidemiology

Kaniadakis

Baldi

Deisboeck

et al. 2020

Preprint

View full text Add to dashboard Cite

A great variety of complex physical, natural and artificial systems are governed by statistical distributions, which often follow a standard exponential function in the bulk, while their tail obeys the Pareto power law. The recently introduced k-statistics framework predicts distribution functions with this feature. A growing number of applications in different fields of investigation are beginning to prove the relevance and effectiveness of k-statistics in fitting empirical data. In this paper, we use k-statistics to formulate a statistical approach for epidemiological analysis. We validate the theoretical results by fitting the derived k-Weibull distributions with data from the plague pandemic of 1417 in Florence as well as partial data (until April 16, 2020) from the COVID-19 pandemic in China. The fact that both the approximate dataset of the Florence plague and the partial data of the Covid-19 pandemic in China are well described by means of the proposed model suggests that the k-deformed Weibull model is relevant and that both datasets faithfully represent the spreading of the epidemics.

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Adaptive Kaniadakis entropy thresholding segmentation algorithm based on particle swarm optimization

Cited by 22 publications

References 20 publications

Research on Multistrategy Improved Evolutionary Sparrow Search Algorithm and its Application

Research on Multistrategy Improved Evolutionary Sparrow Search Algorithm and its Application

The κ-statistics approach to epidemiology

The κ-statistics approach to epidemiology

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