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Adaptive neural networks
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Part 2 of ebook "Measuring technology and mechatronics automation in electrical engineering" provides readers with contents including: hardware-in-the-loop for on-line identification of SSP driving motor; hybrid adaptive fuzzy vector control vector control for single-phase induction motors; hybrid intelligent algorithm based on hierarchical encoding for training of RBF neural network; improved fuzzy neural network for stock market prediction and application; landslide recognition in mountain image based on support vector machine;...
259p
dongmelo
20-05-2024
4
1
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In this paper, a modified feedback error learning approach (called MFEL) is proposed for a nonlinear system. In MFEL, an inverse evolutionary neural (IEN) model that dynamically identifies offline all nonlinear features of the nonlinear system, provides the initial value of a feedforward compensator.
8p
vijeff
01-12-2023
5
3
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This paper proposes a simple adaptive controller for pitch angle control of the variable speed wind turbine. The aim of the controller is to keep the speed of the generator at the rated value when the wind speed is above the nominal value.
8p
vijeff
30-11-2023
5
3
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In this work, we aim to design and evaluate an autoencoder-based communication model with RIS support, which can adapt to changes in the environment and the receiver’s position. Specifically, we use neural networks to present the encoder and decoder of the system and the parameters of these networks are trained to minimize the reconstruction error at the receiver.
10p
visystrom
22-11-2023
6
4
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"Artificial neural networks in real life applications" offers an outlook of the most recent works at the field of the Artificial Neural Networks (ANN), including theoretical developments and applications of systems using intelligent characteristics for adaptability.
395p
haojiubujain08
01-11-2023
6
3
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Ebook "Foundations of soft case-based reasoning" includes content: Introduction, case representation and indexing, case selection and retrieval, case adaptation, case base maintenance, applications.
299p
haojiubujain07
20-09-2023
5
4
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Ebook "Encyclopedia of artificial intelligence" includes content: Adaptive business intelligence, adaptive neuro fuzzy systems, advanced cellular neural networks image processing, agent based intelligent system modeling, ai and ideas by statistical mechanics, an ai walk from pharmacokinetics to marketing, ambient intelligence, ambient intelligence environments,....and other contents.
1676p
haojiubujain07
20-09-2023
5
3
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Ebook "Neural networks - Algorithms, applications, and programming techniques" includes content: Introduction to ANS technology, adaline and madaline, backpropagation, the BAM and the hopfield memory, simulated annealing, the counter propagation network, self organizing maps, adaptive resonance theory, spatiotemporal pattern classification, the neocognitron.
414p
haojiubujain07
20-09-2023
5
2
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Ebook "Machine learning for adaptive many core machines - A practical approach (studies in big data) 2015" includes content: Motivation and preliminaries, GPU machine learning library (GPUMLib), neural networks, handling missing data, support vector machines, incremental hypersphere classifier, non negative matrix factorization, deep belief networks
251p
haojiubujain07
20-09-2023
3
3
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Continued part 1, part 2 of ebook "Neural network programming with Java: Unleash the power of neural networks by implementing professional Java code" provides readers with contents including: forecasting weather; classifying disease diagnosis; clustering customer profiles; pattern recognition (OCR Case); neural network optimization and adaptation; setting up the netbeans environment; setting up the eclipse environment;...
125p
tieulangtran
28-09-2023
6
5
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The purpose of the present paper is to study the computation complexity of deep ReLU neural networks for approximation of functions in H¨older-Nikol’skii spaces. Our results show the advantage of the adaptive method of approximation by deep ReLU neural networks over nonadaptive one.
30p
vimulcahy
18-09-2023
5
4
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This study aims to compare and contrast the performance of Artificial neural network (ANN) and Decision Tree (DT) methods in predicting the compressive strength and slump values of concrete samples. Experimental data used for model building and comparison were obtained from a previous research project.
9p
vifriedrich
30-08-2023
5
3
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Estimating punching shear capacity (PSC) of steel fibre reinforced concrete slabs (SFRCS) is a crucial task in structural design. This study investigates the performances of artificial neural networks trained by the adaptive moment estimation (Adam) method in dealing with the task of interest. To alleviate overfitting problem, decoupled weight decay (AdamW) and L2 regularization (AdamL2) are used. A dataset including 140 samples has been used to train and verify the machine learning approaches.
5p
nhanchienthien
25-07-2023
6
3
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The impact of different rice husk ash contents (5, 10, 20%) on mortar strength is examined at different elevated temperatures (150, 300, 450, 750oC). Based on a 45 experimental result data set, three machine learning algorithms including the Artificial Neural Network (ANN), the Least Squares Support Vector Regression (LS-SVR) and the Multivariate Adaptive Regression Splines (MARS) have been used to model the functional relationship between the mixture components and the compressive strength.
10p
nhanchienthien
25-07-2023
6
4
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The paper investigates the lane following and changing maneuvers of autonomous vehicles in the presence of unknown disturbances, taking into account the dynamic system states and input constraints. The integrated longitudinal-lateral and yaw rate dynamics of the vehicle are simultaneously considered to improve the tracking accuracy and system stability when navigating under critical conditions.
11p
vihawkeye
26-05-2023
12
5
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In this paper, the CNN-based model was developed to identify crack/non-crack images collected on the surface of a concrete structure. The CNN model was adapted from the pre-trained, open-sourced model developed by Google and distributed through TensorFlow.
4p
vifalcon
16-05-2023
10
4
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This paper confirms the practical effect of applying Artificial Neural Networks (ANNs) using Radial basis function (RBF) bases on Sliding mode control (SMC) to control nonlinear systems. The proposed algorithm is put into comparison with the super twisting 2-SMC, which was designed to reduce chattering and increase the performance of conventional SMC.
7p
vidoctorstrange
06-05-2023
9
5
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This paper represents superior properties of advanced control methods such as Fuzzy Logic, Neural network to PID controller for uncertainties systems to achieve good tracking response in real time. All three control methods are based on the feedback error signal that is then calculated on the processor through algorithms and outputting the optimal control signals.
7p
vidoctorstrange
06-05-2023
8
4
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In this paper, we consider the adaptive sliding mode control with radial basis function neural networks for the Omni-directional mobile robot. This is a holonomic robot that can operate easily in small and narrow spaces, due to the ability of flexible rotational and translational moving, simultaneously and independently.
8p
vidoctorstrange
06-05-2023
12
6
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The broad aim of this research project is to optimize planned and emergency maintenance tasks and timings for tram tracks. Consistent with that broad aim, the following specific objectives are identified: Understand the factors affecting the degradation of tram tracks; develop a degradation prediction model for tracks as a function of the influencing factors; evaluate the time and type of maintenance required for deteriorated rail tracks.
101p
runthenight04
02-02-2023
3
1
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