Dynamic Fuzzy Logic Control of GeneticAlgorithm Probabilities

Genetic algorithms are commonly used to solve combinatorial optimizationproblems. The implementation evolves using genetic operators (crossover, mutation,selection, etc.). Anyway, genetic algorithms like some other methods have parameters(population size, probabilities of crossover and mutation) which need to be tune orchosen.In this paper, our project is based on an existing hybrid genetic algorithmworking on the multiprocessor scheduling problem. We propose a hybrid Fuzzy-Genetic Algorithm (FLGA) approach to solve the multiprocessor scheduling problem.The algorithm consists in adding a fuzzy logic controller to control and tunedynamically different parameters (probabilities of crossover and mutation), in anattempt to improve the algorithm performance. For this purpose, we will design afuzzy logic controller based on fuzzy rules to control the probabilities of crossoverand mutation. Compared with the Standard Genetic Algorithm (SGA), the resultsclearly demonstrate that the FLGA method performs significantly better.

On Qualitative Probabilities for Legal Reasoning about Evidence

A crucial aspect of evidential reasoning in crime investigation involves comparing the support that evidence provides for alternative hypotheses. Recent work in forensic statistics has shown how Bayesian Networks (BNs) can be employed for this purpose. However, the specification of BNs requires conditional probability tables describing the uncertain processes under evaluation. When these processes are poorly understood, it is necessary to rely on subjective probabilities provided by experts. Accurate probabilities of this type are normally hard to acquire from experts. Recent work in qualitative reasoning has developed methods to perform probabilistic reasoning using coarser representations. However, the latter types of approaches are too imprecise to compare the likelihood of alternative hypotheses. This paper examines this shortcoming of the qualitative approaches when applied to the aforementioned problem, and identifies and integrates techniques to refine them.

A Complexity Based Model for Quantifying Forensic Evidential Probabilities

An operational complexity model (OCM) is proposed to enable the complexity of both the cognitive and the computational components of a process to be determined. From the complexity of formation of a set of traces via a specified route a measure of the probability of that route can be determined. By determining the complexities of alternative routes leading to the formation of the same set of traces, the odds ratio indicating the relative plausibility of the alternative routes can be found. An illustrative application to a BitTorrent piracy case is presented, and the results obtained suggest that the OCM is capable of providing a realistic estimate of the odds ratio for two competing hypotheses. It is also demonstrated that the OCM can be straightforwardly refined to encompass a variety of circumstances.

Laws of large numbers for non-additive probabilities

We apply the concept of exchangeable random variables to the case of non-additive robability distributions exhibiting ncertainty aversion, and in the lass generated bya convex core convex non-additive probabilities, ith a convex core). We are able to rove two versions of the law of arge numbers (de Finetti's heorems). By making use of two efinitions. of independence we rove two versions of the strong law f large numbers. It turns out that e cannot assure the convergence of he sample averages to a constant. e then modal the case there is a true" probability distribution ehind the successive realizations of the uncertain random variable. In this case convergence occurs. This result is important because it renders true the intuition that it is possible "to learn" the "true" additive distribution behind an uncertain event if one repeatedly observes it (a sufficiently large number of times). We also provide a conjecture regarding the "Iearning" (or updating) process above, and prove a partia I result for the case of Dempster-Shafer updating rule and binomial trials.

Optical transition probabilities and compositional dependence of Judd-Ofelt parameters of Er3+ ions in fluoroindate glass

Fluoroindate glasses containing 1, 2, 3, and 4 mol% ErF3 were prepared in a dry box under an argon atmosphere. Absorption spectra of these glasses at room temperature were obtained. The Judd-Ofelt parameters Ωλ (λ = 2, 4, 6) for f-f transitions of Er3+ ions as well as transition probabilities, branching ratios, radiative lifetimes, and peak cross-sections for stimulated emission of each band were determined. The concentration effect on the intensities is analyzed. The optical properties of the fluoroindate glasses doped with Er3+ ions are compared with those of other glasses described in the literature. © 1995.

Detecting migrants in populations of Rhizoctonia solani anastomosis group 3 from potato in North Carolina using multilocus genotype probabilities

The relative contribution of migration of Rhizoctonia solani anastomosis group 3 (AG-3) on infested potato seed tubers originating from production areas in Canada, Maine, and Wisconsin (source population) to the genetic diversity and structure of populations of R. solani AG-3 in North Carolina (NC) soil (recipient population) was examined. The frequency of alleles detected by multilocus polymerase chain reaction-restriction fragment length polymorphisms, heterozygosity at individual loci, and gametic phase disequilibrium between all pairs of loci were determined for subpopulations of R. solani AG-3 from eight sources of potato seed tubers and from five soils in NC. Analysis of molecular variation revealed little variation between seed source and NC recipient soil populations or between subpopulations within each region. Analysis of population data with a Bayesian-based statistical method previously developed for detecting migration in human populations suggested that six multilocus genotypes from the NC soil population had a statistically significant probability of being migrants from the northern source population. The one-way (unidirectional) migration of genotypes of R. solani AG-3 into NC on infested potato seed tubers from Canada, Maine, and Wisconsin provides a plausible explanation for the lack of genetic subdivision (differentiation) between populations of the pathogen in NC soils or between the northern source and the NC recipient soil populations.

Average control of Markov decision processes with Feller transition probabilities and general action spaces

This paper studies the average control problem of discrete-time Markov Decision Processes (MDPs for short) with general state space, Feller transition probabilities, and possibly non-compact control constraint sets A(x). Two hypotheses are considered: either the cost function c is strictly unbounded or the multifunctions A(r)(x) = {a is an element of A(x) : c(x, a) <= r} are upper-semicontinuous and compact-valued for each real r. For these two cases we provide new results for the existence of a solution to the average-cost optimality equality and inequality using the vanishing discount approach. We also study the convergence of the policy iteration approach under these conditions. It should be pointed out that we do not make any assumptions regarding the convergence and the continuity of the limit function generated by the sequence of relative difference of the alpha-discounted value functions and the Poisson equations as often encountered in the literature. (C) 2012 Elsevier Inc. All rights reserved.

Predicting future risk of asthma exacerbations using individual conditional probabilities

Determination of future risk of exacerbations is a key issue in the management of asthma. We previously developed a method to calculate conditional probabilities (π) of future decreases in lung function by using the daily fluctuations in peak expiratory flow (PEF).

Insular volume abnormalities associated with different transition probabilities to psychosis

Background Although individuals vulnerable to psychosis show brain volumetric abnormalities, structural alterations underlying different probabilities for later transition are unknown. The present study addresses this issue by means of voxel-based morphometry (VBM). Method We investigated grey matter volume (GMV) abnormalities by comparing four neuroleptic-free groups: individuals with first episode of psychosis (FEP) and with at-risk mental state (ARMS), with either long-term (ARMS-LT) or short-term ARMS (ARMS-ST), compared to the healthy control (HC) group. Using three-dimensional (3D) magnetic resonance imaging (MRI), we examined 16 FEP, 31 ARMS, clinically followed up for on average 3 months (ARMS-ST, n=18) and 4.5 years (ARMS-LT, n=13), and 19 HC. Results The ARMS-ST group showed less GMV in the right and left insula compared to the ARMS-LT (Cohen's d 1.67) and FEP groups (Cohen's d 1.81) respectively. These GMV differences were correlated positively with global functioning in the whole ARMS group. Insular alterations were associated with negative symptomatology in the whole ARMS group, and also with hallucinations in the ARMS-ST and ARMS-LT subgroups. We found a significant effect of previous antipsychotic medication use on GMV abnormalities in the FEP group. Conclusions GMV abnormalities in subjects at high clinical risk for psychosis are associated with negative and positive psychotic symptoms, and global functioning. Alterations in the right insula are associated with a higher risk for transition to psychosis, and thus may be related to different transition probabilities.

Estimation of Transition Probabilities in Animal Carcinogenicity Experiments

This paper discusses estimation of the tumor incidence rate, the death rate given tumor is present and the death rate given tumor is absent using a discrete multistage model. The model was originally proposed by Dewanji and Kalbfleisch (1986) and the maximum likelihood estimate of the tumor incidence rate was obtained using EM algorithm. In this paper, we use a reparametrization to simplify the estimation procedure. The resulting estimates are not always the same as the maximum likelihood estimates but are asymptotically equivalent. In addition, an explicit expression for asymptotic variance and bias of the proposed estimators is also derived. These results can be used to compare efficiency of different sacrifice schemes in carcinogenicity experiments.