Search results for "Inference"
showing 10 items of 478 documents
Uncertainty estimation of a complex water quality model: The influence of Box–Cox transformation on Bayesian approaches and comparison with a non-Bay…
2012
Abstract In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised L…
A Project Manager Suitability Parameter in Project Accomplishment
2009
One the most critical aspect in project management is how to assign the project managers (PMs) to projects, especially whenever the PMs can lead more than one project. The present paper proposes a parameter (PME) to evaluate the PM in accomplishing a specific project useful for a next phase of assignment. The PME takes into account the technical skills, the leadership behavior and the relationships with project’s stakeholders. These parameters are aggregated by a Fuzzy Inference System (FIS) that well emulates the decision process of the experts by means of a rule-based inference engine. Moreover, to better define the PME, a procedure, based on the discordance concept, is proposed to compar…
Local Monitor Implementation for Decentralized Intrusion Detection in Secure Multi–Agent Systems
2007
This paper focuses on the detection of misbehav- ing agents within a group of mobile robots. A novel approach to automatically synthesize a decentralized Intrusion Detection System (IDS) as well as an efficient implementation of local monitors are presented. In our scenario, agents perform possi- bly different independent tasks, but cooperate to guarantee the entire system’s safety. Indeed, agents plan their next actions by following a set of logic rules which is shared among them. Such rules are decentralized, i.e. they depend only on configurations of neighboring agents. However, some agents may not be acting according to this cooperation protocol, due to spontaneous failure or tampering.…
E-negotiator based on buyer's surfing pattern
2017
Everyone likes to get the best price, but best price cannot be provided to everyone. This paper proposes an algorithm to provide the best price to the most prospective buyer. E-Negotiation will be based on buyer's activity pattern and surfing behavior. Unlike existing e-negotiation models proposed for B2C, B2B and C2C Ecommerce applications, where the intervention of buyer is present, this paper proposes a system to e-negotiate by just observing buyer's surfing pattern, without depending on his input. Surfing patterns such as sites visited and products surfed will tell the buyer's intention on purchasing the product. The amount of discount for negotiation is generated using a Fuzzy Inferenc…
Bayesian inference analysis of the uncertainty linked to the evaluation of potential flood damage in urban areas.
2012
Flood damage in urbanized watersheds may be assessed by combining the flood depth–damage curves and the outputs of urban flood models. The complexity of the physical processes that must be simulated and the limited amount of data available for model calibration may lead to high uncertainty in the model results and consequently in damage estimation. Moreover depth–damage functions are usually affected by significant uncertainty related to the collected data and to the simplified structure of the regression law that is used. The present paper carries out the analysis of the uncertainty connected to the flood damage estimate obtained combining the use of hydraulic models and depth–damage curve…
Real-time parameter estimation of Zika outbreaks using model averaging
2017
SUMMARYEarly prediction of the final size of any epidemic and in particular for Zika disease outbreaks can be useful for health authorities in order to plan the response to the outbreak. The Richards model is often been used to estimate epidemiological parameters for arboviral diseases based on the reported cumulative cases in single- and multi-wave outbreaks. However, other non-linear models can also fit the data as well. Typically, one follows the so called post selection estimation procedure, i.e., selects the best fitting model out of the set of candidate models and ignores the model uncertainty in both estimation and inference since these procedures are based on a single model. In this…
Quantifying transmission fitness costs of multi-drug resistant tuberculosis.
2021
As multi-drug resistant tuberculosis (MDR-TB) continues to spread, investigating the transmission potential of different drug-resistant strains becomes an ever more pressing topic in public health. While phylogenetic and transmission tree inferences provide valuable insight into possible transmission chains, phylodynamic inference combines evolutionary and epidemiological analyses to estimate the parameters of the underlying epidemiological processes, allowing us to describe the overall dynamics of disease spread in the population. In this study, we introduce an approach to Mycobacterium tuberculosis (M. tuberculosis) phylodynamic analysis employing an existing computationally efficient mod…
Fair Kernel Learning
2017
New social and economic activities massively exploit big data and machine learning algorithms to do inference on people’s lives. Applications include automatic curricula evaluation, wage determination, and risk assessment for credits and loans. Recently, many governments and institutions have raised concerns about the lack of fairness, equity and ethics in machine learning to treat these problems. It has been shown that not including sensitive features that bias fairness, such as gender or race, is not enough to mitigate the discrimination when other related features are included. Instead, including fairness in the objective function has been shown to be more efficient.
CorCast: A Distributed Architecture for Bayesian Epidemic Nowcasting and its Application to District-Level SARS-CoV-2 Infection Numbers in Germany
2021
Timely information on current infection numbers during an epidemic is of crucial importance for decision makers in politics, medicine, and businesses. As information about local infection risk can guide public policy as well as individual behavior, such as the wearing of personal protective equipment or voluntary social distancing, statistical models providing such insights should be transparent and reproducible as well as accurate. Fulfilling these requirements is drastically complicated by the large amounts of data generated during exponential growth of infection numbers, and by the complexity of common inference pipelines. Here, we present CorCast – a stable and scalable distributed arch…
smatr 3 - an R package for estimation and inference about allometric lines
2011
Summary 1. The Standardised Major Axis Tests and Routines (SMATR) software provides tools for estimation and inference about allometric lines, currently widely used in ecology and evolution. 2. This paper describes some significant improvements to the functionality of the package, now available on R in smatr version 3. 3. New inclusions in the package include sma and ma functions that accept formula input and perform the key inference tasks; multiple comparisons; graphical methods for visualising data and checking (S)MA assumptions; robust (S)MA estimation and inference tools.