The contribution deals with a deterministic-based structural optimisation (DBSO). The instroductory part of the paper covers a short overview of optimisation algorithms applicable to deterministic-based problems, general DBSO formulation and a target function(s) pattern for structural design. The following part gives attention to particular problem of general RC (reinforced concrete) cross-sectional design subjected to normal force and bending moments (ULS, i.e. ultimate limit state), where basic cross-sectional characteristics (cross-sectional dimensions, steel bars profiles and types of materials constitute an optimisation space with discrete attributes. The target function (including economical and ecological aspects) and principle problem solution(s) is defined and an illlustrative numerical example of a simple rectangular cross-section design is presented. The solution approach is further augmented to RC frame structures problems and a numerical example of a collector tube design is presented. and Obsahuje seznam literatury
Reliability-Based Structural Optimisation (RBSO) incorporates probabilistic structural reliability analysis into structural optimisation. A sample definition of an RBSO problem and its solution are presented for the optimisation of an RC cross-section, which is subjected to combinations of normal force and bending moments. The presented RBSO algorithm utilizes the LHS (Latin Hypercube Sampling) approximate simulation method for reliability computations. Numerical results for the particular data set are presented. and Obsahuje seznam literatury
There are two basic types of artificial neural networks: Multi-Layer Perceptron (MLP) and Radial Basis Function network (RBF). The first type (MLP) consists of one type of neuron, which can be decomposed into a linear and sigmoid part. The second type (RBF) consists of two types of neurons: radial and linear ones. The radial basis function is analyzed and then used for decomposition of RBF network. The resulting Perceptron Radial Basis Function Network (PRBF) consists of two types of neurons: linear and extended sigmoid ones. Any RBF network can be directly converted to a four-layer PRBF network while any MLP network with three layers can be approximated by a five-layer PRBF network. The new PRBF network is then a generalization of MLP and RBF network abilities. Learning strategies are also discussed. The new type of PRBF network and its learning via repeated local optimization is demonstrated on a numerical example together with RBF and MLP for comparison. This paper is organized as follows: Basic properties of MLP and RBF neurons are summarized in the first two chapters. The third chapter includes novel relationship between sigmoidal and radial functions, which is useful for RBF decomposition and generalization. Description of new PRBF network, together with its properties, is subject of the fourth chapter. Numerical experiments with a PRBF and their requests are given in the last chapters.
This paper discusses a novel approach to tuning 2DOF PID controllers for a positional control system, with a special focus on filters. It is based on the multiple real dominant pole method, applicable to both standard and series PID control. In the latter case it may be generalized by using binomial nth order filters. These offer filtering properties scalable in a much broader range than those allowed by a standard controller. It is shown that in terms of a modified total variance, controllers with higher order binomial filters allow a significant reduction of excessive control effort due to the measurement noise. When not limited by the sampling period choice, a significant performance increase may be achieved by using third order filters, which can be further boosted using higher order filters. Furthermore, all of the derived tuning procedures keep the controller design sufficiently simple so as to be attractive for industrial applications. The proposed approach is applied to the position control of electrical drives, where quantization noise can occur as a result of angular velocity reconstruction using the differentiated outputs of incremental position sensors.
Inland waters are known to be laden with high levels of suspended particulate matter (SPM). Remotely sensed data have been shown to provide a true synoptic view of SPM over vast areas. However, as to date, there is no universal technique that would be capable of retrieving SPM concentrations without a complete reliance on time-consuming and costly ground measurements or a priori knowledge of inherent optical properties of water-borne constituents. The goal of this paper is to present a novel approach making use of the synergy found between the reflectance in the visual domain (~ 400-700 nm) with the near-infrared portion of the spectrum (~ 700-900 nm). The paper begins with a brief discourse of how the shape and spectral dependence of reflectance is determined by high concentrations of SPM. A modeled example is presented to mimic real-world conditions in fluvial systems, with specific absorption and scattering coefficients of the virtual optically active constituents taken from the literature. Using an optical model, we show that in the visual spectral domain (~ 400-700 nm) the water-leaving radiance responds to increasing SPM (0-100 g m-3) in a non-linear manner. Contrarily to the visual spectra, reflectance in the near infrared domain (~ 700-900 nm) appears to be almost linearly related to a broad range of SPM concentrations. To reduce the number of parameters, the reflectance function (optical model) was approximated with a previously experimentally verified exponential equation (Schiebe et al., 1992: Remote sensing of suspended sediments: the Lake Chicot, Arkansas project, Int. J. Remote Sensing, 13, 8, 1487-1509). The SPM term in Schiebe’s equation was expressed as a linear function of top-of-atmosphere reflectance. This made it possible to calibrate the reflectance in the visual domain by reflectance values from the near-IR portion of the spectrum. The possibility to retrieve SPM concentrations from only remote sensing data without any auxiliary ground mea-surements is tested on a Landsat ETM + scene acquired over a reservoir with moderately turbid water with SPM concentrations between 15-70 g m-3. The retrieved concentrations (on average) differ from in-situ measurement by ~ 10.5 g m-3. and Cieľom príspevku je prezentovať alternatívne spracovanie satelitných snímok na odhad koncentrácie suspendovaných sedimentov vo vodných útvaroch. Prvá časť článku sa venuje teórii a fyzikálnej podstate reflektancie a vplyvu prirodzene sa vyskytujúcich opticky aktívnych prvkov vo vode (suspendované sedimenty, pigmenty a rozpustené látky) na reflektanciu snímanú prostriedkami diaľkového prieskumu Zeme. Na modelovom príklade sme ukázali, že so zvyšovaním koncentrácie suspendovaných látok dochádza k saturácii signálu reflektancie.V druhej časti príspevku sme opísali spôsob využitia nelineárnosti vzťahu medzi reflektanciu vo viditeľnej časti (~ 400-700), a kvázi-linearitov v infračervenej časti (~ 700-900 nm) elektromegnetického spektra a koncentrácie suspendovaných sedimentov. Optimalizáciou tohto nelineárneho vzťahu sme odhadli koncentrácie suspendovaných sedimentov pre zdrž Hrušov pri Bratislave s RMSE 10.5 g m-3.
The synoptic overview follows two lines of the core topic: life span development and the strategy of its research. The actual task is to design a life span development theory leading to the recognition and specification of individual development dynamics together with allocation of resources for growth, resilience and coping with losses. Ongoing empirical research point out how this general concept is tested in specific areas, such as cognitive processes, motor activity and emotionality. Is lifespan developmental psychology a special kind of developmental psychology, a general integrative ontogenetic concept, or is, is just one of the orientations in the current research of development? Arguments in current discussions are hinted. One of the main pretensions of life span development theory is to allocate a profile of biology- and culture-based sources of growth, resilience and coping with losses. Pluralism appears to be a general characteristic for changes of postmodernism in the concepts of diversity. The number of papers dealing with both positive and risk factors in the lifespan development context is increasing.
In the real-life engineering practice, non-linear regression models have to be designed rather often. To ensure their technical or physical feasibility, such models may, in addition, require another coupling condition. This paper describes two procedures for designing a specific non-linear model using AI methods. A Radial Basis Functions (RBF) based optimization is presented of the model using Genetic Algorithms (GA). The problem solved was based on practical measurements and experiments. The results presented in the paper can be applied to many technical problems in mechanical and civil engineering and other engineering fields. and Obsahuje seznam literatury
Precise wind energy potential assessment is vital for wind energy generation and planning and development of new wind power plants. This work proposes and evaluates a novel two-stage method for location-specific wind energy potential assessment. It combines accurate statistical modelling of annual wind direction distribution in a given location with supervised machine learning of efficient estimators that can approximate energy efficiency coefficients from the parameters of optimized statistical wind direction models. The statistical models are optimized using differential evolution and energy efficiency is approximated by evolutionary fuzzy rules.