Estimation of Distribution Algorithms (EDAs) is a new area of Evolutionary Computation. In EDAs there is neither crossover nor mutation operators. New population is generated by sampling the probability distribution, which is estimated from a database containing selected individuals of the previous generation. Different approaches have been proposed for the estimation of probability distributio...

In this paper, we show how Estimation of Distribution Algorithms (EDAs) can be applied to the optimization of multivariate functions in continuous domain. First, we describe the relationship between Gaussian network model and multivariate normal densities along with the methods used for the learning and simulation of Gaussian networks. Next, we propose our algorithm that uses only the means and...

The real options technique has emerged as an evaluation tool for investment under uncertainty. It explicitly recognizes future decisions, and the exercise strategy is based on the optimal decisions in future periods. This paper employs the optimal stopping policy derived from real options approach to analyze and evaluate genetic algorithms, specifically for the new branches namely Estimation of...

Estimation of Distribution Algorithms (EDAs) use a probabilistic model of promising solutions found so far to obtain new candidate solutions of an optimization problem. This paper focuses on the design of parallel EDAs. More specifically, the paper describes a method for parallel construction of Bayesian networks with local structures in form of decision trees in the Mixed Bayesian Optimization...

A 17-year-old boy with known moyamoya disease developed an acute subdural hematoma after a mild head trauma. He had been confined to a wheelchair with contracture in the upper and lower extremities due to juvenile rheumatoid arthritis since age 1 year. He had undergone encephalo-duro-arterio-synangiosis (EDAS) on the right and encephalo-myo-synangiosis (EMS) on the left at 13 years of age. He w...

A 54-year-old woman presented to our hospital with progressive motor weakness of the right arm. She had a medical history of systemic lupus erythematosus (SLE) and hypothyroidism. Magnetic resonance imaging indicated a watershed infarction of the left hemisphere. Cervical echogram indicated severe stenosis of the internal carotid artery (ICA) without wall thickening. Cerebral angiography indica...

Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Generative Adversarial Networks (GAN) are generative neural networks which can be trained to implicitly model the probability distribution of given data, and it is possible to sample this distribution. We integrate a GAN into an EDA and evaluate the performance of this s...

سابقه و هدف: در کشور ایران از حدود 5/88 میلیارد مترمکعب آب استحصال‌شده منابع سطحی زیرزمینی، ۸۳ یعنی 5/93 درصد به بخش کشاورزی اختصاص می‌یابد، بزرگ‌ترین مصرف‌کننده است. مصرف رو افزایش معلول جمعیت، سطح زیر کشت تولیدات هست که به‌تبع آن سبب کاهش دسترسی افت ایستابی تخلیه آبخوان‌ها شده آمارها نشان می‌دهند این استراتژیک، تهدید کمیت کیفیت است ­طوری ­که هم ­اکنون تعداد زیادی دشت­ های شرایط بحرانی قرار دا...

© 2015 Egyptian Journal of Neurosurgery. All rights reserved Background: Many forms of indirect cerebral revascularization had been adapted to establish neovascularization in moyamoya disease (MMD) affecting pediatric age group. Objective: The aim of this study was to analyze the clinical outcome and different angiographic responses following combined indirect revascularization [encephaloduroar...

In this paper is proposed a new heuristic approach belonging to the field of evolutionary Estimation of Distribution Algorithms (EDAs). EDAs builds a probability model and a set of solutions is sampled from the model which characterizes the distribution of such solutions. The main framework of the proposed method is an estimation of distribution algorithm, in which an adaptive Gibbs sampling is...