Search results for "A* algorithm"

Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models

2017

Topic models for text analysis are most commonly trained using either Gibbs sampling or variational Bayes. Recently, hybrid variational-Gibbs algorithms have been found to combine the best of both worlds. Variational algorithms are fast to converge and more efficient for inference on new documents. Gibbs sampling enables sparse updates since each token is only associated with one topic instead of a distribution over all topics. Additionally, Gibbs sampling is unbiased. Although Gibbs sampling takes longer to converge, it is guaranteed to arrive at the true posterior after infinitely many iterations. By combining the two methods it is possible to reduce the bias of variational methods while …

A genetic algorithm for combined topology and shape optimisations

2003

A method to find optimal topology and shape of structures is presented. With the first the optimal distribution of an assigned mass is found using an approach based on homogenisation theory, that seeks in which elements of a meshed domain it is present mass; with the second the discontinuous boundaries are smoothed. The problem of the optimal topology search has an ON/OFF nature and has suggested the employment of genetic algorithms. Thus in this paper a genetic algorithm has been developed, which uses as design variables, in the topology optimisation, the relative densities (with respect to effective material density) 0 or 1 of each element of the structure and, in the shape one, the coord…

Traffic fundamentals for A22 Brenner freeway by microsimulation models.

La tesi di dottorato ha avuto come tema lo studio e l’applicazione di un modello di micro-simulazione del traffico in ambito autostradale. Essa si compone di quattro capitoli, con ognuno dei quali si è voluto sintetizzare e descrivere il lavoro di studio e ricerca svolto durante il suddetto corso di Dottorato di Ricerca. L’obiettivo principale del presente lavoro di tesi è stato quello di mettere a punto una metodologia finalizzata all’ottenimento delle relazioni fondamentali di deflusso in ambito autostradale attraverso il software di microsimulazione del traffico Aimsun. Come risulta infatti noto dalla letteratura scientifica, le relazioni fondamentali del deflusso sono utilizzate nel cam…

Capacity-based calculation of passenger car equivalents using traffic simulation at double-lane roundabouts

2018

Abstract Calculation of passenger car equivalents for heavy vehicles represents the starting point for the operational analysis of road facilities and other traffic management applications. This paper introduces a criterion to find the passenger car equivalents that reflect traffic conditions at double-lane roundabouts, where the capacity is typically estimated for each entry lane. Based on the equivalence defined by the proportion of capacity used by vehicles of different classes, the criterion implies a comparison between the capacity that would occur with a traffic demand of passenger cars only and the capacity reached beginning from a demand with a certain percentage of heavy vehicles. …

Multilayer neural networks: an experimental evaluation of on-line training methods

2004

Artificial neural networks (ANN) are inspired by the structure of biological neural networks and their ability to integrate knowledge and learning. In ANN training, the objective is to minimize the error over the training set. The most popular method for training these networks is back propagation, a gradient descent technique. Other non-linear optimization methods such as conjugate directions set or conjugate gradient have also been used for this purpose. Recently, metaheuristics such as simulated annealing, genetic algorithms or tabu search have been also adapted to this context.There are situations in which the necessary training data are being generated in real time and, an extensive tr…

Learning the structure of HMM's through grammatical inference techniques

2002

A technique is described in which all the components of a hidden Markov model are learnt from training speech data. The structure or topology of the model (i.e. the number of states and the actual transitions) is obtained by means of an error-correcting grammatical inference algorithm (ECGI). This structure is then reduced by using an appropriate state pruning criterion. The statistical parameters that are associated with the obtained topology are estimated from the same training data by means of the standard Baum-Welch algorithm. Experimental results showing the applicability of this technique to speech recognition are presented. >

A multi-objective genetic algorithm for the passenger maritime transportation problem

2014

Over the last years, the transportation demand has continuously increased and a further growth is predicted for the next future especially as regards the maritime sector. As a consequence, shipping companies will be asked to improve the supplied services in order to assure a high quality and time-effective goods and passengers transportation, deriving at the same time their own benefits by minimizing costs. Therefore, the optimization of routes and schedules together with the fleet deployment take a meaningful role on companies profitability and efficiency. In such a perspective, the present paper proposes a multi-objective mathematical programming model to determine a set of routes and sch…

Normal and Abnormal Tissue Classification in Positron Emission Tomography Oncological Studies

2018

Positron Emission Tomography (PET) imaging is increasingly used in radiotherapy environment as well as for staging and assessing treatment response. The ability to classify PET tissues, as normal versus abnormal tissues, is crucial for medical analysis and interpretation. For this reason, a system for classifying PET area is implemented and validated. The proposed classification is carried out using k-nearest neighbor (KNN) method with the stratified K-Fold Cross-Validation strategy to enhance the classifier reliability. A dataset of eighty oncological patients are collected for system training and validation. For every patient, lesion (abnormal tissue) and background (normal tissue around …

New insights into the OCST problem

2009

This paper considers the Euclidean variant of the optimal communciation spanning tree (OCST) problem. Researches have analyzed the structure of the problem and found that high quality solutions prefer edges of low cost. Further, edges pointing to the center of the network are more likely to be included in good solutions. We add to the literature and provide additional insights into the structure of the OCST problem. Therefore, we investigate properies of the whole tree, such as node degrees and the Wiener index. The results reveal that optimal solutions are structured in a star-like manner. There are few nodes with high node degrees, these nodes are located next to the graph's center. The m…

Fuzzified Tree Search in Real Domain Games

2011

Fuzzified game tree search algorithm is based on the idea that the exact game tree evaluation is not required to find the best move. Therefore, pruning techniques may be applied earlier resulting in faster search and greater performance. Applied to an abstract domain, it outperforms the existing ones such as Alpha-Beta, PVS, Negascout, NegaC*, SSS*/ Dual* and MTD(f). In this paper we present experimental results in real domain games, where the proposed algorithm demonstrated 10 percent performance increase over the existing algorithms.