Search results for "Identification"
showing 10 items of 1600 documents
Identification of parameters of the Jiles-Atherton model by neural networks
2011
In this paper a procedure for the identification of the parameters of the Jiles–Atherton (JA) model is presented. The parameters of the JA model of a material are found by using a neural network trained by a collection of hysteresis curves, whose parameters are known. After a presentation of the Jiles–Atherton model, the neural network and the training procedure are described and the method is validated by using some numerical, as well as experimental, data.
Comparison of Attention Behaviour Across User Sets through Automatic Identification of Common Areas of Interest
2020
Eye tracking is used to analyze and compare user behaviour within numerous domains, but long duration eye tracking experiments across multiple users generate millions of eye gaze samples, making th ...
Company in a Global Environment and Intangible Assets
2017
The article discusses the nature and material scope of intangible assets. The author presented that these are key factors in the process of doing business in the global market. The paper also presents possibilities of their identification in the accounting system. To solve the presented problem, the author used methods of analysis of literature, content of legal regulations, and a method of comparison and inference.
A Stigmergic Guiding System to Facilitate the Group Decision Process
2012
The paper presents a stigmergic approach to engineer a guiding system to facilitate the complex problem of designing the group decision processes. The system aims to provide contextual, actionable recommendations based on the knowledge and past experience of its users as recorded in a collaborative working environment implemented around the concept of stigmergic systems. Through an agent-based socio-simulation experiment we have demonstrated already the feasibility of this approach. The paper illustrates how the simulation results are transferred into a guiding system that facilitates the group decision process design through iterative queries reformulations for the identification, represen…
Moving Averages for Market Timing
2016
This paper begins by presenting the moving average methodology of detecting the direction of a trend and identifying turning points in the trend in real time. The paper then proceeds to introduce the general weighted moving average, derives some of its key properties, and discusses how to quantitatively assess the two important characteristics of a moving average: the average lag time and the smoothness. Finally the paper aims to give an overview of some specific types of moving averages used in market timing. These types include regular moving averages, moving averages of moving averages, and mixed moving averages with less lag time. Different types of moving averages are compared to each …
On identification of separable kernel systems
1979
An identification procedure for special separable kernel systems is presented. The suitable definition of adequateness of a signal leads to a systematic treatment of the choice of inputs for identification.
Benchmarking open data efforts through indices and rankings: Assessing development and contexts of use
2022
Abstract This paper aims to provide a broad perspective on the development of benchmarking open data efforts through indices and rankings over the years, both at the level of countries and allowing for a cross-country comparison. The methodology follows a systematic search for the relevant resources, their classification and identification of six open data benchmarks to be further analyzed, the identification of their key components through decomposition, their description, and identifying the similarities and differences. Three major groups of indices and four periods that characterize the efforts to benchmark and measure the development of open data are identified, where the first measure…
Optimization of image parameters using a hyperspectral library application to soil identification and moisture estimation
2009
The growing number of sensors raises questions about the image parameters required for the application, soil identification and moisture estimation. Hyperspectral images are also known to contain highly redundant information. Hence not all the spectral bands are needed for the satisfactory classification of the soil types. Hence, the work was aimed at obtaining these optimal spectral bands for identifying the soil types and to use these spectral bands to estimate the moisture content of the soils using the method proposed by Whiting et.al.
Accelerated dinuclear palladium catalyst identification through unsupervised machine learning.
2021
Although machine learning bears enormous potential to accelerate developments in homogeneous catalysis, the frequent need for extensive experimental data can be a bottleneck for implementation. Here, we report an unsupervised machine learning workflow that uses only five experimental data points. It makes use of generalized parameter databases that are complemented with problem-specific in silico data acquisition and clustering. We showcase the power of this strategy for the challenging problem of speciation of palladium (Pd) catalysts, for which a mechanistic rationale is currently lacking. From a total space of 348 ligands, the algorithm predicted, and we experimentally verified, a number…
Simulation and Parameter-Identification of the Closed-Loop Cardiovascular System by the Use of a Nonlinear Mathematical Model
1981
Abstract A non-linear model of human cardio-vascular system, which includes the short-term pressure regulation mechanism was mathematically derived and implemented on a PDP-11/45 in a block-oriented, interactive programming language. In this way the behaviour of the arterial and venous pressures, cardiac output, stroke volume, total peripheral resistance and heart-rate under ergometric workload was studied by simulation, and experimentally proved, that the model matches the system with good accuracy. In a second phase the parameters of the model were identified by the use of the output-error method. For this purpose a non-linear system identification programming package was applied. The par…