Search results for "probabilistic"
showing 10 items of 380 documents
IMPROVEMENTS IN THE SYSTEMS-BASED MODELS GENERATOR SIGEM
1994
Program generators, for us, are computer programs that produce other computer programs. SIGEM is an expert system program generator that can help in the modeling process of real systems. It is associated with a methodology well adapted to modeling practice. In this paper, we present and compare this methodology with other similar ones. Static models (databases), dynamic models, rule-based expert systems, literal and/or numerical variables, probabilistic uncertainty in data and in functions, dimensioned variables, discrete event simulation, and other related problems can be treated with this methodology. We suggest a systems modeling methodology and a programming tool to increase generality …
On the fractional probabilistic Taylor's and mean value theorems
2016
In order to develop certain fractional probabilistic analogues of Taylor's theorem and mean value theorem, we introduce the nth-order fractional equilibrium distribution in terms of the Weyl fractional integral and investigate its main properties. Specifically, we show a characterization result by which the nth-order fractional equilibrium distribution is identical to the starting distribution if and only if it is exponential. The nth-order fractional equilibrium density is then used to prove a fractional probabilistic Taylor's theorem based on derivatives of Riemann-Liouville type. A fractional analogue of the probabilistic mean value theorem is thus developed for pairs of nonnegative rand…
Inverted Repeats in Viral Genomes
2004
We investigate 738 complete genomes of viruses to detect the presence of short inverted repeats. The number of inverted repeats found is compared with the prediction obtained for a Bernoullian and for a Markovian control model. We find as a statistical regularity that the number of observed inverted repeats is often greater than the one expected in terms of a Bernoullian or Markovian model in several of the viruses and in almost all those with a genome longer than 30,000 bp.
Reliability Analysis of a Controlled Stage-Constructed and Reinforced Embankment on Soft Ground Using 2D and 3D Models
2020
Geosynthetic reinforcement has become a very practical technique to improve geotechnical structure safety. In spite of improved soil behavior, structures are affected by uncertainties related to soil and reinforcement material properties. This paper aims to present a reliability analysis in order to take statistical information (uncertainties) into account in a safety analysis of reinforced embankments. The analysis was used in a case study on a controlled stage-constructed embankment on soft ground in order to investigate its probabilistic stability. Modeling was performed by commercial geotechnical software usage (GeoStudio and RocScience packs, SIGMA/W+SLOPE/W and SLIDE³, respectively) a…
On the influence of using binary and distributed information for 2D hydraulic model calibration and uncertainty evaluation
2013
Floods are considered the most frequent natural disaster world-wide and may have serious socio economic impacts in a community. In order to accomplish flood risk mitigation, flood risk analysis and assessment are required to provide information on current or future flood hazard and risks. Hazard and risk maps involve different data, expertise and effort, depending also on the end-users. More or less advanced deterministic approaches can be used, but intuitively probabilistic approaches seem to be more correct and suited for modelling flood inundation given typical uncertainties. Two very important matters remain open for research: the calibration of hydraulic models (oriented towards the es…
Frequency Prediction of Functions
2012
Prediction of functions is one of processes considered in inductive inference. There is a "black box" with a given total function f in it. The result of the inductive inference machine F( ) is expected to be f(n+1). Deterministic and probabilistic prediction of functions has been widely studied. Frequency computation is a mechanism used to combine features of deterministic and probabilistic algorithms. Frequency computation has been used for several types of inductive inference, especially, for learning via queries. We study frequency prediction of functions and show that that there exists an interesting hierarchy of predictable classes of functions.
Probabilistic whereabouts of the "quantum potential"
2011
We review major appearances of the functional expression $\pm \Delta \rho ^{1/2}/ \rho ^{1/2}$ in the theory of diffusion-type processes and in quantum mechanically supported dynamical scenarios. Attention is paid to various manifestations of "pressure" terms and their meaning(s) in-there.
IRT Modeling of Decomposed Student Learning Patterns in Higher Education Economics
2019
Researchers have spent decades arguing how to measure improvements in learning within formal settings, where achievements are intended and presupposed, in a reliable and valid way. Repeated measures are required to investigate improvements of any kind. Students usually take a multiple-choice test at least twice with the difference between the two measurements indicating how much they have learned. Walstad and Wagner (J Econ Educ 47:121–131, 2016) presented a new approach to gathering more information about different learning patterns by decomposing these difference measures. They describe the patterns of positive learning (PL) and negative learning (NL), i.e., the development from not knowi…
H2S: A Secure and Efficient Data Aggregative Retrieval Scheme in Unattended Wireless Sensor Networks
2009
In unattended wireless sensor networks, data are stored locally and retrieved on demand. To efficiently transmit the collector’s retrieval results, data are aggregated along being forwarded. The data confidentiality and integrity should be protected at the intermediate nodes. End-to-end encryption or hop-by-hop encryption based schemes are not efficient. Straightforward homomorphic encryption based scheme is not compromise resilient. To achieve all the desires, we propose a scheme - H2S by making use of both homomorphic secret sharing and homomorphic encryption. The security and efficiency of our scheme are justified by extensive analysis.
Parameter Uncertainty in Shallow Rainfall-triggered Landslide Modeling at Basin Scale: A Probabilistic Approach
2014
Abstract This study proposes a methodology to account for the uncertainty of hydrological and mechanical parameters in coupled distributed hydrological-stability models for shallow landslide assessment. A probabilistic approach was implemented in an existing eco-hydrological and landslide model by randomizing soil cohesion, friction angle and soil retention parameters. The model estimates the probability of failure through an assumed theoretical Factor of Safety (FS) distribution, conditioned on soil moisture content. The time-dependent and spatially distributed FS statistics are approximated by the First Order Second Moment (FOSM) method. The model was applied to the Rio Mameyes Basin, loc…