Beyond Moments: Extending the Maximum Entropy Principle to Feature Distribution Constraints

Baggenstoss, Paul M.

doi:10.3390/e20090650

Cited by 9 publications

(2 citation statements)

References 38 publications

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“…The maximum entropy principle is extensively applied in many disciplines [ 28 , 29 , 30 , 31 , 32 ]. In information theory, if there is a discrete random variable, X , with possible values of { x1, x2, …, xn }, and probability mass function, P(X ), the entropy, H, of X is defined as follows:

where E is the expectation operator, r is the logarithmic base, which generally takes a value of two [ 33 , 34 , 35 ] (in this study, r = 2).…”

Section: Methodsmentioning

confidence: 99%

Entropy-Based Method to Evaluate Contact-Pressure Distribution for Assembly-Accuracy Stability Prediction

Chen

Jin

Shang

et al. 2019

Entropy

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Assembly accuracy and accuracy stability prediction are significant research directions for improving the reliability and efficiency of precision assembly. In this study, an improved method for assembly accuracy stability prediction, based on the contact-pressure distribution entropy, is presented. By using the contact-pressure distribution as the evaluation parameter instead of the strain-energy distribution, the improved method can not only predict the assembly accuracy of precision assembly more efficiently, but also predict the stability of the assembly accuracy with variations in the ambient temperature. The contact pressure has a clearer mechanical significance than strain energy density in the assembly process, which can be used to distinguish the actual contact area from the contact surface. Hence, the improved method is more efficient and accurate than the original. This study utilizes the same case used in the original method and an additional case from the actual production process to verify the improved method. The correctness and validity of the improved method are proved by these case studies.

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where E is the expectation operator, r is the logarithmic base, which generally takes a value of two [ 33 , 34 , 35 ] (in this study, r = 2).…”

Section: Methodsmentioning

confidence: 99%

Entropy-Based Method to Evaluate Contact-Pressure Distribution for Assembly-Accuracy Stability Prediction

Chen

Jin

Shang

et al. 2019

Entropy

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“…Duplicate presence records were removed using basic settings along with random seed feature. Ten replicates were run for both models and logistic outputs were selected using Baggenstoss 2018 [2] ; Presse et al 2013 [39] ; Phillips and Dudik 2008. Jackknife approach was adopted to determine the importance of the variables used in the model (Hoenes and Bender 2010; Yost et al 2009) [20,48] .…”

Section: Climate Data Extraction and Analysismentioning

confidence: 99%

Partial altitudinal movement of Himalayan Bulbul Pycnonotus leucogenys in Himalayan Siwalik range

Kumar¹,

Kler²,

Singh³

et al. 2022

Pharma Innovation

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Himalayan Bulbul Pycnonotus leucogenys is widely spread in the Himalayan Siwalik range but information is available on its migratory behavioural patterns. Hence, a two-year study was undertaken to investigate its distribution range of the species in the summer and winter seasons in Punjab and Himachal Pradesh. A total of twenty variables including 19 bioclimatic variables and elevation were selected for the development of Species distribution Modelling (SDM). Occurrence records of P. leucogenys in summer and winter were processed at the Maximum entropy model (MaxEnt) using the ENMeval data package. The results suggested a downward movement from the upper Siwalik Himalayan ranges to the lower Siwalik in winter, and with return migration movement in summer. However, a large fraction of the distribution range was found overlapping in both the models, which suggests partial altitudinal migration of P. leucogenys. The data recorded on the ground subordinate the finding of the model. A wide range of tolerance for bioclimatic variables was observed in P. leucogenys, however temperaturerelated factors played a vital role in the variation in the species distribution range in the annual cycle of partial migration. The finding of this study would be a valuable reference for future studies on ecological and behavioral aspects of partial-migration of bird species in the Himalaya.

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Data fusion for Uncertainty Quantification with Non-Intrusive Polynomial Chaos

Pepper

Montomoli

Sharma

2021

Computer Methods in Applied Mechanics and Engineering

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Beyond Moments: Extending the Maximum Entropy Principle to Feature Distribution Constraints

Cited by 9 publications

References 38 publications

Entropy-Based Method to Evaluate Contact-Pressure Distribution for Assembly-Accuracy Stability Prediction

Entropy-Based Method to Evaluate Contact-Pressure Distribution for Assembly-Accuracy Stability Prediction

Partial altitudinal movement of Himalayan Bulbul Pycnonotus leucogenys in Himalayan Siwalik range

Data fusion for Uncertainty Quantification with Non-Intrusive Polynomial Chaos

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