scholarly journals Development of Seismic Damage Evaluation System for Bridge Structures by using Damage Transition Probability Model.

1999 ◽  
Vol 48 (10) ◽  
pp. 1179-1186
Author(s):  
Akihiko KANEYOSHI ◽  
Takashi YASUMOTO ◽  
Ayaho MIYAMOTO
Keyword(s):  
Evaluation System ◽  
Transition Probability ◽  
Probability Model ◽  
Seismic Damage ◽  
Damage Evaluation ◽  
Bridge Structures ◽  
Transition Probability Model

scholarly journals A theory of memory for binary sequences: Evidence for a mental compression algorithm in humans

2021 ◽  
Vol 17 (1) ◽  
pp. e1008598
Author(s):  
Samuel Planton ◽  
Timo van Kerkoerle ◽  
Leïla Abbih ◽  
Maxime Maheu ◽  
Florent Meyniel ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Model Comparison ◽  
Transition Probability ◽  
Probability Model ◽  
Working Memory Capacity ◽  
Compression Algorithm ◽  
Binary Sequences ◽  
Fixed Sequence ◽  
Transition Probability Model ◽  
Human Adults

Working memory capacity can be improved by recoding the memorized information in a condensed form. Here, we tested the theory that human adults encode binary sequences of stimuli in memory using an abstract internal language and a recursive compression algorithm. The theory predicts that the psychological complexity of a given sequence should be proportional to the length of its shortest description in the proposed language, which can capture any nested pattern of repetitions and alternations using a limited number of instructions. Five experiments examine the capacity of the theory to predict human adults’ memory for a variety of auditory and visual sequences. We probed memory using a sequence violation paradigm in which participants attempted to detect occasional violations in an otherwise fixed sequence. Both subjective complexity ratings and objective violation detection performance were well predicted by our theoretical measure of complexity, which simply reflects a weighted sum of the number of elementary instructions and digits in the shortest formula that captures the sequence in our language. While a simpler transition probability model, when tested as a single predictor in the statistical analyses, accounted for significant variance in the data, the goodness-of-fit with the data significantly improved when the language-based complexity measure was included in the statistical model, while the variance explained by the transition probability model largely decreased. Model comparison also showed that shortest description length in a recursive language provides a better fit than six alternative previously proposed models of sequence encoding. The data support the hypothesis that, beyond the extraction of statistical knowledge, human sequence coding relies on an internal compression using language-like nested structures.

Application of FTRF in Cascading Failure Probability Model in Adverse Weather

2013 ◽  
Vol 336-338 ◽  
pp. 471-474
Author(s):  
Shi Guang ◽  
Hai Jing Yang ◽  
Qi Wei Wang ◽  
Yan Jin
Keyword(s):  
Failure Probability ◽  
Power Flow ◽  
Transition Probability ◽  
Probability Model ◽  
First Line ◽  
Line Load ◽  
State Transfer ◽  
Adverse Weather ◽  
Load Rate ◽  
Transition Probability Model

In allusion to the issues of system line state transfer that may arise in adverse weather, a new method of probability calculation is proposed. In a statistical analysis, this article firstly defines that failure probability of the first line subjects to Poisson distribution. Secondly, we figure out the power flow transferring distribution after first line fault, according to the method of Flow Transferring Relativity Factor (FTRF), and combine with the protective possibility so as to build the probability model between the load rate and protection action. Then, the method defines the severity of line load rate. Finally, the approach constructs the line state transition probability model considering direct and indirect factors in adverse weather. The effectiveness and correctness of the proposed method are verified by simulation based on IEEE 39-node system.

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