wavelet neural network control for maximization of energy capture in grid connected variable spe
Process simulation of oxy combustion for maximization of energy output using ASPEN plus
... Effect of varying RGIBBS temperature on pollutant formation 3.2 Effect of variation in mass of oxygen in IN-GAS stream The stoichiometric mass of oxygen required for complete combustion of 100kg of ... because the energy must be expended in heating the increased mass of nitrogen since the oxygen and nitrogen are in a fixed ratio in air ISSN 2076-2895 (Print), ISSN 2076-2909 (Online) ©2014 International ... M.S degree in Aerospace Engineering from University of Southern California His research interests are in the application of computational fluid dynamics in the study of chemical looping combustion...
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Process simulation and maximization of energy output in chemical looping combustion using ASPEN plus
... linear with increase in coal feeding rate In general, such linearity is not expected for actual industrial-level scale-up since the ASPEN Plus system modeling software neglects miscellaneous energy ... Effect of varying the oxygen carrier feeding rate on energy output of four types of coals with 100 kg/h coal feeding rate The effect of varying the oxygen carrier feeding rate on energy output of ... feeding rate increases above a certain threshold value, the marginal increase in energy output by increasing the OC rate becomes extremely small The red line in Figure represents the baseline...
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Báo cáo nghiên cứu khoa học: " NEURAL NETWORK CONTROL OF PNEUMATIC ARTIFICIAL MUSCLE MANIPULATOR FOR KNEE REHABILITATION" pps
... Toward intelligent PID control, in Int., Conf., Automatic, pp 1-9, (1992) [12] Yamada, T., Yabuta, T., Neural network controller using autotuning method for nonlinear functions, in IEEE Trans., Neural ... the combination will take the advantage of simplicity of PID control and the neural network s powerful capability of learning, adaptability and tackling nonlinearity And the input signal of the ... Structure of proposed controller However, if severe nonlinearity is involved in the controlled process, a nonlinear control scheme will be more useful, particularly in case of high nonlinearity of the...
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a comparison of neural network architectures for
... 93.43% for the combination features data set This slight improvement in accuracy comes at a price of an increase in time requirements, since the running time increased by over a minute It is interesting ... Configurable attributes of the network include the number of input neurons, the number of hidden layers, the number of neurons in each hidden layer, the number of output neurons, the learning rate (α), ... between nodes in layers, with every node in the layer being connected to every node in the following layer, and the initial weights for these connections are initialized to random values in the [-1,...
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neural network models for formation and control
... nonlinear transformations required for making an inverse dynamics model of a nonlinear controlled object One is that they are computed by nonlinear information processing within the dendrites of ... coordinates of the desired trajectory must be reinterpreted in terms of a corresponding set of body coordinate, such as joint angles or muscle lengths (coordinates transformation in Fig 1) Finally, ... succeeded in learning control of the robotic manipulator by an inverse-dynamics model made of a three-layer neural network (Fig 5) $\frac{A^{u}}{*,4}$ In this network, nonlinear transformation...
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Báo cáo hóa học: " Research Article Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition" pot
... coupling,” in Proceedings of the 1997 Conference on Advances in Neural Information Processing Systems 10, pp 507–513, Denver, Colo, USA, 1998 [5] V Schetinin, J Schult, B Scheidt, and V Kuriakin, ... Kuriakin, “Learning multiclass neural- network models from electroencephalograms,” in Knowledge-Based Intelligent Information and Engineering Systems, vol 2773 of Lecture Notes in Computer Science, ... outperforms the multiclass system in terms of the predictive accuracy on the test data For instance, for 24 samples a gain in the accuracy is equal to 9.5% When the number of samples is 60, the gain...
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A self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
... Sketches of the Working of the Network In order to help the understanding of the principles with which the neocognitron performs pattern recognition, we will make rough sketches of the working of the ... Thin-lined squares in the figure stand for individual cell-planes (except in layer Uc3 in which each cellplane contains only one cell) The magnitude of the output of each individual cell is indicated ... is of great use not only as an inference upon the mechanism of the brain but also to the field of engineering One of the largest and long-standing difficulties in designing a pattern-recognizing...
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Adaptive control and neural network control of nonlinear discrete time systems
... adaptive control of linear systems has motivated the rapid growing interest in nonlinear adaptive control from the end of 1980’s In particular, adaptive control of nonlinear systems using feedback linearization ... problem in adaptive control had remained open till the Nussbaum gain was first introduced in [77] for adaptive control of first order continuous-time systems In [45], adaptive control of high order linear ... tracking performance However, it is interesting and challenging in discrete-time adaptive control to fully compensate for the effect of nonparametric nonlinear model uncertainties for exact tracking...
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Adaptive neural network control of discrete time nonlinear systems
... algorithms such as BP, sufficient off-line training must be performed before neural network controllers are put into the systems 1.1 Adaptive Neural Network Control of Nonlinear Systems Because their universal ... Recently neural networks have been made particularly attractive and promising for applications to modelling and control of nonlinear systems For neural network controller design of general nonlinear ... [62] In last decades, in continuous-time domain, feedback linearization technique [63, 64, 1.1 Adaptive Neural Network Control of Nonlinear Systems 65], backstepping design [66], neural network control...
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Evolution of artificial neural network controller for a boost converter
... application of neural networks in the field of power electronics has been documented in papers [4]-[5] A novel concept of application of neural network for generation of optimal switching pattern in voltage ... use of neural networks for identification and control of power converters In addition the results obtained show the feasibility of implementing complex nonlinear control laws for dc-dc switching ... control scheme of ANN, then the configuration of neural network i s discussed In the following sections, the mathematical modeling, neural network design, principal of DLPSO, implementation of...
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Tài liệu Báo cáo " DETERMINING FLOW ENERGY AND EROSION COEFFICIENT FOR CLASSIFICATION OF POTENTIAL EROSION IN BINH DINH PROVINCE " ppt
... Distribution of flow energy (Y) at river basins in Binh Dinh Province (unit: %) Total in province At Lai River Basin At Kon River Basin At La Tinh River Basin At Ha Thanh River Basin
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Tài liệu Evolving the neural network model for forecasting air pollution time series pdf
... rate of 0.1 Recombination of parents using double point crossover Reinsertion of offsprings with elitism Binary mutation with rates 0.02 and 0.04 Evaluation of offsprings (Eq.3) Fig The main stages ... selection of individuals (BGAs) for recombination was done using stochastic universal sampling (provides zero bias and minimum spread) and the recombination using the discrete recombination of real/integer ... for prediction by training the network to output the next day value of NO2 (T+24 h, where T is the forecasting point) of a forecasted pollutant, given an input vector containing earlier air quality...
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Tài liệu Thesis "Neural Network Control" doc
... number of hidden units M is sufficiently large 1.2.2 Training The process of tuning the neural network weights in order to achieve a certain kind of performance of the neural network is called training ... stopping instead of regularisation as noted below in section 2.2.6 2.2.6 Neural Network Training During training we minimise the error function introduced in section 2.2.1 This way the neural network ... start weights for neural network train network for 50 epochs end choose best of above networks train network using early stopping as termination Early Stopping It is important for the network to...
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designing and implementing a neural network library for handwriting detection, image analysis etc
... There are two interesting functions, TrainNetwork and RunNetwork, for training and running the network The input to the TrainNetwork function is an object of TrainingData class The TrainingData class ... Propagation neural networks The major interfaces in the model are briefed below INetworkFactory An interface to define a neural network factory INeuron The interface for defining a neuron INeuronStrategy ... 5.4 A Neural Network In BrainNet library Now, let us see how the Neural Network is implemented Any concrete neural network should implement the INeuralNetwork interface INeuralNetwork interface...
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a neural network model for limb trajectory formation
... learning phase First, the learning procedure was repeated by making use of local coding instead of coarse coding (one plan unit for each pixel for a total of 225 plan units) After learning the ... many point attractors In other words these networks naturally exhibit certain dynamic properties In our case, the network was instructed during training to produce certain output patterns for six ... control Annual INNS Meeting, Boston, Mass, pp 332 Eckmiller R (1988) Concept of a 4-joint machine with neural network control for the generation of two-dimensional trajectories First Annual INNS...
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báo cáo hóa học: " A biologically inspired neural network controller for ballistic arm movements" ppt
... and for the controller training process Simulating the Internal Model: the training phase During the training, the system automatically and randomly chooses the starting and ending points of the ... muscular forces, exclusively on the basis of kinematic information such as the starting and ending point of the movements; • the capacity of the neural controller to acquire the internal model of the ... ending points coordinates, become the new data for the training of the network (phase 3) In this way, a mapping between muscular activations and points of the working space can be attained The...
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Báo cáo toán học: " Criteria for robustness of heteroclinic cycles in neural microcircuits" potx
... invariant subspace containing si , typical points y ∈ si will have a neighbourhood in Ic that contain no points in any other Ij In a neighbourhood of this y, perturbations of f in XI have no restriction ... represents both the intrinsic firing and that due to interaction with the other cells in the network These systems have a very rich set of invariant subspaces because of the invariance of all subspaces ... have introduced a testable criterion for robustness for a given cycle of heteroclinic connections within constrained settings—this test involves finding the connection scheme and then applying...
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Báo cáo hóa học: " Research Article Link Quality-Based Transmission Power Adaptation for Reduction of Energy Consumption and Interference" pot
... Networking For IEEE 802.15.4, energy consumption is critical due to its use in wireless sensor networks Therefore, we mainly discuss interference reduction for IEEE 802.11 and energy saving for ... with the lowest E Depending on what P value we use, we will optimize for different things For instance, if we are interested in minimizing energy emission we use the following formula: P = PRF , (2) ... that achieves the minimum energy consumption or emission for delivering a certain amount of information based on link PDR-tables We explore the maximum potential reduction of energy emission and...
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Báo cáo hóa học: " Multihop Medium Access Control for WSNs: An Energy Analysis Model" potx
... hops resulting in an overall distance of R Linear path Sink Figure 2: A simple linear multihop model in a large network producing a linear path The large network may contain several linear paths ... G increases, nanoMAC with a nonpersistence of performs very well for a wide range of G, Multihop MAC for WSNs: An Energy Analysis Model 533 ×10−4 linearly The increase of reception continues for ... studied and worked in the United States, United Kingdom, and Finland He has been principal investigator in several international research projects, including initiating and leading several large...
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Multi-beneficial for mitigation of climate change in Vietnam and Indochina countries by development of biomass energy project
... MULTI-BENEFICIAL FOR MITIGATION OF CLIMATE CHANGE IN VIETNAM AND INDOCHINA COUNTRIES BY DEVELOPMENT OF BIOMASS ENERGY PROJECT The 1st Joint Coordinating Com m ittee (JCC) M eeting January 7th, ... Chemistry JO IN T C O O R D INA TING C O M M IT T E E (JCC) M E ET IN G AGENDA Time: Venue: 09:0C January 07, 2013 Faculty of Chemistry, VNU-HN _ y Morning Opening Greeting - Prof Luu Van ... tsid e d u rin g th e m eetin g ) 1/5/2013 Multi-beneficial Measure for Mitigation of Climate Change in Vietnam and Indochina Countries by Cultivation-Production-Utilization of Biomass Energy Osaka...
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