Optimization Analysis of Two-Dimensional Animation Special Effects Design by Style Transfer Algorithm

The application of 5G communication technology and ultra- wideband technology in animation design has gradually improved the level of animation special effects design, and made the style transfer algorithm a research hotspot. The original two-dimensional animation special effects design cannot solve the problem of special effects optimization, and the special effects after optimization are poor. Therefore, this paper proposes a style transfer algorithm based on 5G communication to optimize and analyze the design of two-dimensional animation special effects. Firstly, ultra-wideband communication technology and animation technology are used to obtain the design parameters of animation special effects, and the design scheme is transformed through style transfer , and judge the special effects scheme according to the animation characteristics, and discard irrelevant 3D information. Then, according to the ultra- wide communication technology, the change rate and display effect of the special effect are analyzed, and compared with the actual reception effect, and adjusted Parameters and indicators for 2D animation special effects design. The special effect design results show that under the conditions of 5G network and ultra-wide communication, the style transfer algorithm can improve the realization effect of animation special effects. The lifting rate is greater than the actual design requirements, which can meet the needs of special effects design

Оптимизация управления автономной энергетической системы с помощью роевых алгоритмов

Представленная научно-квалификационная работа посвящена решению задачи оптимизации управления автономной энергетической системы с помощью роевых алгоритмов. В ходе выполнения работы были разработаны компьютерные модели элементов фотоэлектрической системы, с помощью которых осуществлялись исследования разработанных алгоритмов. В работе предложены следующие алгоритмы: - алгоритм пчелиного роя с ручной настройкой параметров; - алгоритм пчелиного роя с мета-оптимизатором на основе генетического алгоритма. Результаты исследования показали улучшение качества управления в режиме экстремального регулирования мощности при применении алгоритмов роевого интеллекта, в сравнении со стандартным алгоритмом.The presented scientific and qualification work is devoted to solving the problem of optimizing the management of an autonomous energy system using swarm algorithms. In the course of the work, computer models of the elements of the photovoltaic system were developed, with the help of which studies of the developed algorithms were carried out. The following algorithms are proposed: - Bee swarm algorithm with manual settings; - A bee swarm algorithm with a meta-optimizer based on a genetic algorithm. The results of the study showed an improvement in the quality of control in the mode of extreme power control when using swarm intelligence algorithms, in comparison with the standard algorithm

Emerging trends in optimal structural health monitoring system design: From sensor placement to system evaluation

This paper presents a review of advances in the field of Sensor Placement Optimisation (SPO) strategies for Structural Health Monitoring (SHM). This task has received a great deal of attention in the research literature, from initial foundations in the control engineering literature to adoption in a modal or system identification context in the structural dynamics community. Recent years have seen an increasing focus on methods that are specific to damage identification, with the maximisation of correct classification outcomes being prioritised. The objectives of this article are to present the SPO for SHM problem, to provide an overview of the current state of the art in this area, and to identify promising emergent trends within the literature. The key conclusions drawn are that there remains a great deal of scope for research in a number of key areas, including the development of methods that promote robustness to modelling uncertainty, benign effects within measured data, and failures within the sensor network. There also remains a paucity of studies that demonstrate practical, experimental evaluation of developed SHM system designs. Finally, it is argued that the pursuit of novel or highly efficient optimisation methods may be considered to be of secondary importance in an SPO context, given that the optimisation effort is expended at the design stage

Deconvolution of complex spectra into components by the bee swarm algorithm

The bee swarm algorithm is adapted for the solution of the problem of deconvolution of complex spectral contours into components. Comparison of biological concepts relating to the behaviour of bees in a colony and mathematical concepts relating to the quality of the obtained solutions is carried out (mean square error, random solutions in the each iteration). Model experiments, which have been realized on the example of a signal representing a sum of three Lorentz contours of various intensity and half-width, confirm the efficiency of the offered approach

Optimization of the Cascade with Two Additional Product Flows for the Simultaneous Concentration of Intermediate Molybdenum Isotopes

A technique has been developed for optimizing multiflow cascades to obtain highly concentrated intermediate molybdenum isotopes. A computational experiment was carried out to separate a mixture of molybdenum isotopes. Various cases for the separation of molybdenum isotopes in cascades with large step separation coefficients corresponding to gas centrifuges were considered. It is shown that using of the bee swarm optimization has an advantage over the Hook-Jeeves method. © 2020 American Institute of Physics Inc.. All rights reserved

Fuzzy-multiple tasks of multicriterial optimization in risk conditions .

Approaches to solving the optimization problem and solving a fuzzy multicriteria optimization problem under risk conditions are considered. To assess risks in fuzzy conditions, it is proposed to supplement the system of constraints of a standard decision-making task with a set of restrictions on possible losses, namely, for selected scenarios, to build a model of their consequences (damages) as functions of control parameters and impose expert limitations on an acceptable level of relative damage for each scenario

Optimizing PEMFC model parameters using ant lion optimizer and dragonfly algorithm: A comparative study

This paper introduced two optimization algorithms which are Ant Lion Optimizer (ALO) and Dragonfly Algorithm (DA) for extracting the Proton Exchange Membrane Fuel Cell (PEMFC) polarization curve parameters. The results produced by both algorithms are being compared to observe their performance. As a results, the ALO shows great performance compared to DA. Furthermore, these results also being compared with the results of the other reported metaheuristics algorithms. The ALO and DA presented competitive results

Dataflow actor network partitioning for multiple FPGAS

Dataflow actor network is used to display the relation between different actors in a directed graph. It is suitable for modelling signal and video processing in software applications. In this paper, the use of dataflow actor network is extended to the hardware implementation of streaming applications via dataflow actor network partitioning for multiple FPGAs based on the number of cuts, connection workload, resource utilization ratio and latency. Multiple FPGAs partitioning is often required for implementing design with large logic count, for cost reduction, multi clock and multi power domains design implementation. The motivation of using the dataflow actor network is due to the nature of the network which closely resembles the structural view and the inter-connections of a design at the architecture level. This representation in the form of a dataflow actor network is suitable for implementing graph partitioning algorithms. The KL algorithm, GA, PSO, SA and WOA are used for single objective partitioning while the MOPSO, MOSA and MOWOA have been used for multi objective partitioning. The objective of this study is to develop partitioning algorithm suitable for use in dataflow actor network and to determine the appropriate partitioning criteria. Results showed that SA has better performance as compared to other partitioning algorithm for single objective partitioning. On the other hand, for multi objective partitioning the MOPSO has better performance for small design while MOSA has better performance for larger design

The deconvolution of complex spectra by artificial immune system

© Published under licence by IOP Publishing Ltd. An application of the artificial immune system method for decomposition of complex spectra is presented. The results of decomposition of the model contour consisting of three components, Gaussian contours, are demonstrated. The method of artificial immune system is an optimization method, which is based on the behaviour of the immune system and refers to modern methods of search for the engine optimization