Search results for "object"
showing 10 items of 1888 documents
Baļķu skaita, izmēru un formu noteikšana no fotogrāfijas
2015
Maģistra darba ietvaros tika izpetītas iespējas – kā var veikt veikt analīzi fotogrāfijām ar baļķiem. Lai mērķi sasniegt tika definētas prasības algoritmam, kuras aprakstīs – kadus paramētrus ir nepieciešams nolasīt no fotografijas, kadas ir prasības apparatūrai un kāds ir pieeņemams kļudu limenis. Papildus tika definētas prasības ievaddatiem. Tika aprakstīti iespējami soļi, kuros var sadalīt atpazīšanas algoritmu un detalizēti aprakstīts iespējams risinājums katram solim. Darba ietvaros tika izpetīti pieejamie riķi problēmas risināšanai, aprakstīti rīku priekšrocības un trūkumi. Darba rezultāta tika ieguts teoretisks pamats programmas izveidošanai un izveidots programmas pirmais prototips.
Survey of methods to visualize alternatives in multiple criteria decision making problems
2012
When solving decision problems where multiple conflicting criteria are to be considered simultaneously, decision makers must compare several different alternatives and select the most preferred one. The task of comparing multidimensional vectors is very demanding for the decision maker without any support. Different graphical visualization tools can be used to support and help the decision maker in understanding similarities and differences between the alternatives and graphical illustration is a very important part of decision support systems that are used in solving multiple criteria decision making problems. The visualization task is by no means trivial because, on the one hand, the grap…
Verbal ordinal classification with multicriteria decision aiding
2008
Abstract Professionals in neuropsychology usually perform diagnoses of patients’ behaviour in a verbal rather than in a numerical form. This fact generates interest in decision support systems that process verbal data. It also motivates us to develop methods for the classification of such data. In this paper, we describe ways of aiding classification of a discrete set of objects, evaluated on set of criteria that may have verbal estimations, into ordered decision classes. In some situations, there is no explicit additional information available, while in others it is possible to order the criteria lexicographically. We consider both of these cases. The proposed Dichotomic Classification (DC…
Ant Colony Models for a Virtual Educational Environment Based on a Multi-Agent System
2008
We have designed a virtual learning environment where students interact through their computers and with the software agents in order to achieve a common educational goal. The Multi-Agent System (MAS) consisting of autonomous, cognitive and social agents communicating by messages is used to provide a group decision support system for the learning environment. Learning objects are distributed in a network and have different weights in function of their relevance to a specific educational goal. The relevance of a learning object can change in time; it is affected by students', agents' and teachers' evaluation. We have used an ant colony behavior model for the agents that play the role of a tu…
ELECTRE III to dynamically support the decision maker about the periodic replacements configurations for a multi-component system
2013
The problem tackled by the present paper concerns the selection of the elements of a repairable and stochastically deteriorating multi-component system to replace (replacements configuration) during each scheduled and periodical system stop within a finite optimization cycle, by ensuring the simultaneous minimization of both the expected total maintenance cost and the system unavailability. To solve the considered problem, a combined approach between multi-objective optimization problem (MOOP) and multi-criteria decision making (MCDM) resolution techniques is proposed. In particular, the @e constraint method is used to single out the optimal Pareto frontier whereas the ELECTRE III multi-cri…
Integration of Two Multiobjective Optimization Methods for Nonlinear Problems
2003
In this paper, we bring together two existing methods for solving multiobjective optimization problems described by nonlinear mathematical models and create methods that benefit from both heir strengths. We use the Feasible Goals Method and the NIMBUS method to form new hybrid approaches. The Feasible Goals Method (FGM) is a graphic decision support tool that combines ideas of goal programming and multiobjective methods. It is based on the transformation of numerical information given by mathematical models into a variety of feasible criterion vectors (that is, feasible goals). Visual interactive display of this variety provides information about the problem that helps the decision maker to…
Interactive MCDM Support System in the Internet
1998
NIMBUS is an interactive multiobjective optimization system. Among other things, it is capable of solving complicated real-world applications involving nondifferentiable and nonconvex functions. We describe an implementation of NIMBUS operating in the Internet, where the World- Wide Web (WWW) provides a graphical user interface. Different kind of visualizations of alternatives produced are available for aiding in the solution process.
Probabilistic Logic under Coherence‚ Model−Theoretic Probabilistic Logic‚ and Default Reasoning in System P
2016
We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore how probabilistic reasoning under coherence is related to model-theoretic probabilistic reasoning and to default reasoning in System P. In particular, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Moreover, we show that probabilistic reasoning under coherence is a generalization of default reasoning in System P. That is, we provide a new probabilistic semantics for System P, which neither uses infinitesimal probabilities nor atomic bound (or bi…
Probabilistic Logic under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning
2001
We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore the relationship between coherence-based and model-theoretic probabilistic logic. Interestingly, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Crucially, we even show that probabilistic reasoning under coherence is a probabilistic generalization of default reasoning in system P. That is, we provide a new probabilistic semantics for system P, which is neither based on infinitesimal probabilities nor on atomic-bound (or also big-stepped) probabil…
Semantic Analysis of the Driving Environment in Urban Scenarios
2021
Understanding urban scenes require recognizing the semantic constituents of a scene and the complex interactions between them. In this work, we explore and provide effective representations for understanding urban scenes based on in situ perception, which can be helpful for planning and decision-making in various complex urban environments and under a variety of environmental conditions. We first present a taxonomy of deep learning methods in the area of semantic segmentation, the most studied topic in the literature for understanding urban driving scenes. The methods are categorized based on their architectural structure and further elaborated with a discussion of their advantages, possibl…