The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper it is proposed the methodology of analytic design of the optimum structure for stochastic control system used on multi-degree-of-freedom stand simulator of spacecraft motion in the presence of deterministic and stochastic disturbances acting on it.
Artificial Immune Recognition System (AIRS) is an algorithm inspired by animal immune system in the biological world. It is specialized in solving pattern recognition problems. Heating, Ventilation and Air Conditioning (HVAC) systems are widely installed in modern buildings to provide the occupants with a satisfactory indoor environment. HVAC systems are the some of the most power consuming equipment...
Estimating short-term power load is a fundamental issue in the power distribution system. Since short-term power load is related to many parameters such as weather conditions, and time. The aim of this study is to determine the relevant parameters in estimating short-term power load not only in order to decrease the computational cost, but also to achieve higher success rates. Furthermore, by using...
This study aims at developing an intelligent agent that can recognize user-specific emotions and can self-evolve. Previous studies have explored several methods to develop the model and improve the results while maintaining the feasibility of real-time implementation for later stages. We evolved the emotion recognition module by using Genetic Programming (GP) and explored several optimizations. We...
This paper presents a knee torque estimation in non-pathological gait cycle at stance phase. Comparative modelling by using dynamics model and neural network model is discussed. Dynamics modelling is constructed by using simple two degree of freedom dynamics with Newtonian calculation approach and more complex four degree of freedom dynamics with Lagrangian calculation approach. Neural network based...
The prosthetic knees have been improved and developed to support the amputee to be able to walk as normal people and help them on a daily basis. This research is concerned with a swing phase of a semi-active prosthetic knees utilizing magnetorheological (MR) damper. Although the referred work which use a neural network predictive control (NNPC) has a satisfying results with low error, it has a possibility...
The paper deals with the problem of stability during the solving of pattern recognition tasks from the point of view of transformation groups. It shows the possibility to avoid the necessity of regularization by using the geometric equaffine Lorentz transformation, exploiting as example the alpha-procedure.
Forecasting the returns of stock markets is gaining importance nowadays in finance. For this aim, in the last decade, Artificial Neural Networks (ANN) have been widely used to forecast stock market movements. In Baltic countries, artificial neural networks are not commonly used in predicting financial failures. This study aims using artificial neural networks to predict OMX Baltic Benchmark GI (OMXBBGI)...
The problems of organization of engineering education on the basis of the competence approach are considered. It is argued that the ideas and principles of this approach only partially meet the needs of training an engineer in the conditions of the modern development of science, technique, technology, production and it manifests itself in a whole series of contradictions arising when projecting a...
The PID control algorithm is the most used industrial control method owing to its simplicity and ease of use. However, tuning PID parameters is not trivial and many methods have been reported in literature. This paper seeks to show a machine learning approach using multivariate regression with gradient descent and the normal equation. The first order cruise control system is used as an example and...
Possible approaches to building the information and mathematical models to evaluate of the effectiveness and quality of the University are discussed in this paper. We characterize cycle of university management, determine the factors affecting the performance activity of universities, identify indicators of assessment of effectiveness and quality, formulate the problem of university management through...
In medical science, sleep stages are the main criteria to define the disorders and have crucial role on diagnostic. In this sense, accurate sleep stage classification plays important role due to provide better report on medications and diagnoses. In this study, EEG signals are classified by a rule based machine learning algorithm; Decision Tree with the ensemble and classical machine learning idea...
A technique and algorithms for early detection of the started attack and subsequent blocking of malicious traffic are proposed. The primary separation of mixed traffic into trustworthy and malicious traffic was carried out using cluster analysis. Classification of newly arrived requests was done using different classifiers with the help of received training samples and developed success criteria.
An accurate detection of spectrum opportunities is a key factor in governing the efficient spectrum usage in a cognitive radio (CR) system. Energy detection based spectrum sensing has been widely used due to its ease of implementation with lower computational complexity; however, its robustness and performance are highly affected by the noise uncertainty. In the present work, a real time hardware...
Some problems of thermodynamic, hydraulic and thermal calculations of the thermal state analysis and performance of the liquid-propellant rocket engine design using neural network modeling are detected. There are presented some applications of neural-network algorithms using in thermal calculations of the LRE chamber such as the simulation of hydraulic non-uniformity of fuel distribution among the...
Generative models are widely used for unsupervised learning with various applications, including data compression and signal restoration. Training methods for such systems focus on the generality of the network given limited amount of training data. A less researched type of techniques concerns generation of only a single type of input. This is useful for applications such as constraint handling,...
In this paper, Self-adaptive Differential Evolutionary Extreme Learning Machine (SaDE-ELM) was proposed as a new class of learning algorithm for single-hidden layer feed forward neural network (SLFN). In order to achieve good generalization performance, SaDE-ELM calculates the error on a subset of testing data for parameter optimization. Since SaDE-ELM employs extra data for validation to avoid the...
Nowadays with the rapid development of network-based services and users of the internet in everyday life, intrusion detection becomes a promising area of research in the domain of security. Intrusion detection system (IDS) can detect the intrusions of someone who is not authorized to the present computer system automatically, so intrusion detection system has emerged as an essential component and...
To overcome the unsatisfying trend prediction results of network public opinion in the present research, this paper put forward a method of Levenberg-Marquardt-based Back-Propagation (LM-BP) neural network algorithm to predict the network public opinion trend. Taking the microblog as the research object, the effectiveness and reliability of the method are proved with some real data in this article...
This paper introduces an efficient probabilistic approach with RSSI fingerprinting for Indoor Localization. A Shannon's Entropy based access points (APs) selection is considered. Once the APs selection is performed, a probability is assigned to each training fingerprint based on RSSI measurements. Then, the user's location is estimated as a combination of training positions weighted with their corresponding...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.