Applications of the Sufficiency Principle in Acceleration of Neural Networks Trainig

One of the problems in AI tasks solving by neurocomputing methods is a considerable training time. This problem especially appears when it is needed to reach high quality in forecast reliability or pattern recognition. Some formalised ways for increasing of networks’ training speed without loosing of precision are proposed here. The offered approaches are based on the Sufficiency Principle, which is formal representation of the aim of a concrete task and conditions (limitations) of their solving [1]. This is development of the concept that includes the formal aims’ description to the context of such AI tasks as classification, pattern recognition, estimation etc.

Systems Analysis: the Structure-and-Purpose Approach Based on Logic-linguistic Formalisation

Systems analysis (SA) is widely used in complex and vague problem solving. Initial stages of SA are analysis of problems and purposes to obtain problems/purposes of smaller complexity and vagueness that are combined into hierarchical structures of problems(SP)/purposes(PS). Managers have to be sure the PS and the purpose realizing system (PRS) that can achieve the PS-purposes are adequate to the problem to be solved. However, usually SP/PS are not substantiated well enough, because their development is based on a collective expertise in which logic of natural language and expert estimation methods are used. That is why scientific foundations of SA are not supposed to have been completely formed. The structure-and-purpose approach to SA based on a logic-and-linguistic simulation of problems/purposes analysis is a step towards formalization of the initial stages of SA to improve adequacy of their results, and also towards increasing quality of SA as a whole. Managers of industrial organizing systems using the approach eliminate logical errors in SP/PS at early stages of planning and so they will be able to find better decisions of complex and vague problems.

A Fractional Analog of the Duhamel Principle

Mathematics Subject Classification: 35CXX, 26A33, 35S10

Application of Subordination Principle to Log-Harmonic alpha-spirallike Mappings

MSC 2010: 30C45, 30C55

Applications of Subordination Principle to Log-Harmonic Mappings

MSC 2010: 30C45, 30C55

Hamilton’s Principle with Variable Order Fractional Derivatives

MSC 2010: 26A33, 70H25, 46F12, 34K37 Dedicated to 80-th birthday of Prof. Rudolf Gorenflo

Maximum Principle and Its Application for the Time-Fractional Diffusion Equations

MSC 2010: 26A33, 33E12, 35B45, 35B50, 35K99, 45K05 Dedicated to Professor Rudolf Gorenflo on the occasion of his 80th anniversary

Duality in Constrained DC-Optimization via Toland’s Duality Approach

2000 Mathematics Subject Classification: 90C48, 49N15, 90C25

CORE: A Multi-Purpose Programming Contest Repository System

Яни Чаушев, Милослав Средков, Красимир Манев - Всяко състезание по програмиране използва множество софтуерни инструменти за управление на процесите по време на състезанието. Въпреки че тези инструменти обикновено покриват спецификите на конкретния вид състезание задоволително, те рядко адресират трудностите на дългосрочното съхранение на данни и оперативната съвместимост. В тази статия е представен един софтуерен инструмент адресиращ тези проблеми. Вместо комплексна система, касаеща всички аспекти на състезанието, CORE е централизирано хранилище за съхраняване и поддържане на необходимите за различни състезания данни. Представени са основните му елементи, текущото състояние на реализацията и перспективите за развитие на системата.

On Principle Eigenvalue for Linear Second Order Elliptic Equations in Divergence Form

2002 Mathematics Subject Classification: 35J15, 35J25, 35B05, 35B50

Minimum Description Length Principle in Discriminating Marginal Distributions

2010 Mathematics Subject Classification: 94A17, 62B10, 62F03.