In this study, the feedforward neural networks (FFNNs) were proposed to forecast the multi-day-ahead streamflow. The parameters of FFNNs model were optimized utilizing genetic algorithm (GA). Moreover, discrete wavele...
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In this study, the feedforward neural networks (FFNNs) were proposed to forecast the multi-day-ahead streamflow. The parameters of FFNNs model were optimized utilizing genetic algorithm (GA). Moreover, discrete wavelet transform was utilized to enhance the accuracy of FFNNs model's forecasting. Therefore, the wavelet-based feedforward neural networks (WFFNNs-GA) model was developed for the multi-day-ahead streamflow forecasting based on three evolutionary strategies [i.e., multi-inputmulti-output (MIMO), multi-input single-output (MISO), and multi-input several multi-output (MISMO)]. In addition, the developed models were evaluated utilizing five different statistical indices including root mean squared error, signal-to-noise ratio, correlation coefficient, Nash-Sutcliffe efficiency, and peak flow criteria. Results provided that the statistical values of WFFNNs-GA model based on MISMO evolutionary strategy were superior to those of WFFNNs-GA model based on MISO and MIMO evolutionary strategies for the multi-day-ahead streamflow forecasting. Results indicated that the performance of WFFNNs-GA model based on MISMO evolutionary strategy provided the best accuracy. Results also explained that the hybrid model suggested better performance compared with stand-alone model based on the corresponding evolutionary strategies. Therefore, the hybrid model can be an efficient and robust implement to forecast the multi-day-ahead streamflow in the Chellif River, Algeria.
Transmitter designs based on partial channel state information (CSI) have become increasingly attractive in multi-antenna wireless communication systems. To capture partial CSI statistics at the transmitter, we rely o...
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Transmitter designs based on partial channel state information (CSI) have become increasingly attractive in multi-antenna wireless communication systems. To capture partial CSI statistics at the transmitter, we rely on a channel amplitude information (CAI) model, based on which we aim for maximizing the random channel's average mutual information. Due to the high computational complexity required for such optimal transmissions, we resort to reduced complexity practical schemes and derive necessary and sufficient conditions for these alternatives to achieve maximal average mutual information.
Admission control has been widely utilized to alleviate network congestion. However, most current studies choose the admissible users based on instantaneous channel information. Due to the time-varying characteristics...
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ISBN:
(纸本)9789082797015
Admission control has been widely utilized to alleviate network congestion. However, most current studies choose the admissible users based on instantaneous channel information. Due to the time-varying characteristics of wireless channels, the admissible user set changes quickly, which complicates network management and renders heavy operational costs. This motivates us to take the stability of the admissible user set into account in admission control, thus leading to a long-term admission control problem. In this paper, we consider a joint long-term admission control and beamforming problem in a downlink network consisting of one multi-antenna base station (BS) and multiple single-antenna users. To maintain a relatively stable admissible user set and minimize the power cost for the admissible users to achieve their quality-of-service levels, we jointly optimize the admissible users, the BS transmit beamformers, and the switching frequency of each user's admissible status in a given time period. To handle this challenging non-convex problem, we first design a sequential convex approximation (SCA) algorithm to iteratively compute a stationary solution. To facilitate algorithm's implementation, we further employ the alternating direction method of multipliers to come up with an efficient, semi-closed-form update of each SCA problem.
This paper presents two new space time block codes (STBCs) with quasi orthogonal structure for an open loop multi-input single-output (MISO) systems. These two codes have been designed to transmit from three or four a...
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ISBN:
(纸本)9781509025268
This paper presents two new space time block codes (STBCs) with quasi orthogonal structure for an open loop multi-input single-output (MISO) systems. These two codes have been designed to transmit from three or four antennas at the transmitter and be given to one antenna at the receiver. In this paper first, the proposed codes are introduced and their structures are investigated. This is followed by the demonstration of how the decoder decodes half of transmitted symbols independent of the other half. The last part of this paper discusses the simulation results, makes performance comparison against other popular approaches and concludes that the proposed solutions offer superiority.
Maximizing the sum-rate in multicell multiple inputsingleoutput (MISO) systems is a non convex and NP-hard problem. Most existing algorithms trying to solve this problem are suboptimal with high computational cost a...
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ISBN:
(数字)9781665484800
ISBN:
(纸本)9781665484800
Maximizing the sum-rate in multicell multiple inputsingleoutput (MISO) systems is a non convex and NP-hard problem. Most existing algorithms trying to solve this problem are suboptimal with high computational cost and high system interaction overhead. In this paper, we propose a coordinated beamforming (CB) scheme based on multi-agent reinforcement learning (MARL) to maximize the sum-rate of the multicell MISO systems with limited information feedback and exchange. Specifically, the training of the proposed MARL network is guided by the actual sum-rate of the multiple cells, and the execution is performed totally locally by using the local channel quality information feedback. Simulation results show that compared to the existing distributed coordinated beamforming scheme, the proposed scheme achieves similar performance by using much reduced information overhead.
Modern greenhouse creates suitable crop growth conditions through changing inside temperature, humidity, solar radiation, concentration of carbon dioxide and other environmental factors to raise production and increas...
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ISBN:
(纸本)9781538629185
Modern greenhouse creates suitable crop growth conditions through changing inside temperature, humidity, solar radiation, concentration of carbon dioxide and other environmental factors to raise production and increase economic *** greenhouse microclimate environment model can not only simulate the behavior of a system well but also design the inside controller suitably to be applied to the greenhouse production. The temperature system in a greenhouse microclimate environment can be regarded as a multi-input single-output hybrid system. In this paper, the system was described by Auto Regressive Moving Average model with e Xternal inputs(ARMAX). The test data were analyzed for the correlation of input variables and output variable. Then, by means of fading memory recursive least squares, the parameters of the model were identified. Finally, the model was simulated and tested. The actual values were fitted by simulation values and the fitting degree reached 0.91 which showed the model was effective.
The hybrid signal is used to identify the multi-input single-output (MISO) Hammerstein model. The hybrid signal consists of Gaussian signal and random signal, and the identification process is divided into two stages,...
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ISBN:
(纸本)9798350321050
The hybrid signal is used to identify the multi-input single-output (MISO) Hammerstein model. The hybrid signal consists of Gaussian signal and random signal, and the identification process is divided into two stages, namely, the stage of dynamic linear part and the stage of static nonlinear part. Firstly, the correlation analysis method is used to identify the linear part parameters. Then, for the parameters of the nonlinear part and the output noise model, an extended stochastic gradient algorithm with forgetting factor (FF-ESG) is adopted to deal with the issue that the convergence of stochastic gradient algorithm is slow. Theoretical analysis and experiments show that the presented method can identify the MISO Hammerstein model with moving average noise and obtain good identification accuracy.
In this paper,we propose a 36-quadrature amplitude modulation(QAM)superposition modulation technique that is featured with uneven symbol probability by nonlinear precoding,named nonlinear coded nonuniform superpositio...
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In this paper,we propose a 36-quadrature amplitude modulation(QAM)superposition modulation technique that is featured with uneven symbol probability by nonlinear precoding,named nonlinear coded nonuniform superposition(NCNS)*** aim is to alleviate the nonlinearity effect caused by high instantaneous power in multi-input single-output(MISO)visible light communication(VLC)system,with an uneven probabilistic-shaped *** transmitter includes two LEDs to send signals independently,and the receiver uses a photo detector to receive the superposed QAM *** experiment results show that NCNS has a better robustness against nonlinearity than pulse amplitude modulation 4,approximately gaining a 16% increase in maximum usable peak-to-peak voltage and a 33% enlargement in dynamic range *** is a simple but effective approach to solve the bandwidth limits related to signal power and hopefully be applied in large power VLC systems such as underwater VLC,or to improve the robustness against power fluctuation.
Due to its high efficiency and reduced emissions, new zero-emission hybrid electric vehicles have been selected as an attractive challenge for future transport applications. New zero -emission hybrid electric, on the ...
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Due to its high efficiency and reduced emissions, new zero-emission hybrid electric vehicles have been selected as an attractive challenge for future transport applications. New zero -emission hybrid electric, on the other hand, has some major drawbacks from the complicated charging process. The hybrid electrical fuel cell system is introduced as the main source to intelligently control multi-source activities. An ultra-capacitor system is selected as the energy recovery assistance to monitor the fuel cell's fast transient and peak power during critical periods. To regulate energy demand and supply, an intelligent energy management system is proposed and tested through several constraints. The proposed approach system aims to act quickly against sudden circumstances related to hydrogen depletion in the prediction of the required fuel consumption basis. The proposed strategy tends to define the proper operating system according to energy demand and supply. The obtained results show that the designed system meets the targets set for the energy management unit by referring to an experimental velocity database.
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