The focus of this study is under the auspices of China Steel Corporation, Taiwan, in carrying out the national energy policy of 2025 Non-Nuclear Home. Under this policy, an estimated 600 offshore wind turbines will be...
详细信息
The focus of this study is under the auspices of China Steel Corporation, Taiwan, in carrying out the national energy policy of 2025 Non-Nuclear Home. Under this policy, an estimated 600 offshore wind turbines will be installed by 2025. In order to carry out the wind energy project effectively, a preliminary study must be conducted. In this article, we investigated the influence of the wake effect on the efficiency of the turbines' layout in a windfarm. A distributed genetic algorithm is deployed to study the wind turbines' layout in order to alleviate the detrimental wake effect. In the current stage of this research, the historical weather data of weather stations near the site of the 29th windfarm, Taiwan, were collected by Academia Sinica. Our wake effect resilient optimized windfarm showed superior performance over that of the conventional windfarm. Additionally, an operation cost minimization process is also demonstrated and implemented using an ant colony optimization algorithm to optimize the total length of the power-carrying interconnecting cables for the turbines inside the optimized windfarm.
In view of the problems that traditional hotel management and service quality are easily affected by service personnel, and the check-in and check-out procedures are cumbersome, a smart hotel management system based o...
详细信息
ISBN:
(纸本)9781665483285;9781665483292
In view of the problems that traditional hotel management and service quality are easily affected by service personnel, and the check-in and check-out procedures are cumbersome, a smart hotel management system based on the combination of IoT and artificial intelligence technology is developed. First, process data collection is used to decompose it into relatively independent Sub-projects, and then use the design structure matrix to express the relationship between the sub-projects, and use the corresponding algorithm to identify the iterative relationship, which provides a feasible idea for project planning and process monitoring. Networking technology realizes centralized control and management of access control and hotel equipment, realizes unmanned service in the whole process from check-in to check-out, and improves efficiency by 7.8%.
In order to eliminate the blocking effect of block compressed sensing algorithm, an optimization algorithm of block compressed sensing observation matrix based on block target is studied. The theory of block compresse...
详细信息
In order to eliminate the blocking effect of block compressed sensing algorithm, an optimization algorithm of block compressed sensing observation matrix based on block target is studied. The theory of block compressed sensing is to segment the original image with fixed size to obtain the sub blocks, arrange the texture of each sub block, use the compressed sensing observation matrix to sample each sub block, and optimize the observation matrix of block compressed sensing to eliminate the blocking effect. The block target method uses sparse orthogonal basis to make the processed block target conform to sparsity and orthogonality. The sparse coefficient vector is obtained by the basis inverse transformation, and the reflection coefficient of block target is obtained by using the sparse coefficient vector to optimize the observation matrix of block compressed sensing. The experimental results show that the peak signal-to-noise ratio (PSNR) is higher than 31dB when the algorithm is applied to image reconstruction, and the relative support set error of different sparsity and observation times is low, which can effectively eliminate the blocking effect of block compressed sensing algorithm.
The sheet beam traveling-wave tube (SBTWT) with staggered double vane (SDV) structure has attracted much attention as a board band and powerful terahertz and millimeter-wave source. In this paper, the velocity taper f...
详细信息
ISBN:
(纸本)9781538682883
The sheet beam traveling-wave tube (SBTWT) with staggered double vane (SDV) structure has attracted much attention as a board band and powerful terahertz and millimeter-wave source. In this paper, the velocity taper for SDV structure is optimized with a recently proposed swarm-intelligence (SI) based optimization algorithm named dragonfly algorithm (DA) in order to enhance the beam-wave interaction efficiency in sheet beam TWT. The optimization result of this algorithm is compared with other commonly used algorithms. The taper optimized with DA is verified with CST particle in cell (PIC) simulations. The efficiency of the optimized structure has been greatly increased in both optimization and PIC simulations.
It is not perfect in view of the fact that the information guidance system of parking spaces in large and medium-sized parking lots at present, it is difficult to find a empty parking spaces in parking lots. One of th...
详细信息
ISBN:
(纸本)9781665404457
It is not perfect in view of the fact that the information guidance system of parking spaces in large and medium-sized parking lots at present, it is difficult to find a empty parking spaces in parking lots. One of the problems is large amount of calculation in traditional Dijkstra algorithm. In this paper, the improved Dijkstra algorithm is presented and optimized to find the best parking path with the purpose of looking for the nearest free parking space based on the layout model in parking lot parking guidance. The experiments show that it can find the optimal parking space and the optimal parking path by the improved Dijkstra algorithm, and improve the parking efficiency.
A patent pool strategy was proposed for use in the electric vehicle cell industry to manage patent licensing disputes and litigation. How to promote EV cell innovation diffusion under a patent pool scenario is unclear...
详细信息
A patent pool strategy was proposed for use in the electric vehicle cell industry to manage patent licensing disputes and litigation. How to promote EV cell innovation diffusion under a patent pool scenario is unclear. We introduced an innovation diffusion channel model comprising different players with patent licensing relationships and market competition relationships following evolutionary game analysis and simulation. We found the interlinked factors that influenced evolutionary stable strategies with a sensitivity test on all factors to identify the important and unimportant factors. To achieve the maximum return for the players, an optimization algorithm was introduced to find the maximum weighted object function. The decision and policy makers could focus on important factors such as improving the technology's competitive advantages, delivering more profits to its licensees with reasonable licensing fees, and finding the best patent pool strategy with the support of the optimization algorithm
Electric vehicle cell industry is an emerging area with fierce competition on technical innovation, in which the patent holder can choose different innovation diffusion options to maximize the return;however, the stra...
详细信息
Electric vehicle cell industry is an emerging area with fierce competition on technical innovation, in which the patent holder can choose different innovation diffusion options to maximize the return;however, the strategy is unclear in certain scenarios. We tried to explain the question of how to maximize the patent holder's return by appropriate patent license strategy to promote EV cell innovation diffusion, when competition and patent licensing relationship exist in the supply chain. A multistage and multichannel diffusion model of EV cell comprising the patent holder, EV cell producer and EV producers is developed;the evolutionary game is analyzed considering the competition among same stage players and patent licensing relationship among different stage players;and an optimization algorithm is introduced to find the maximum weighted object function of the patent holder. We established the multistage and multichannel diffusion model and found a nonlinear complex relationship between patent holder object function and the key factors including patent royalty pricing and innovation advantage coefficient;in addition, an optimization algorithm is developed based on adopters' decision-making related with competition and patent licensing.
Source signals often contain various hidden waveforms, which further provide precious information. Therefore, detecting and capturing these waveforms is very important. For signal decomposition (SD), discrete Fourier ...
详细信息
Source signals often contain various hidden waveforms, which further provide precious information. Therefore, detecting and capturing these waveforms is very important. For signal decomposition (SD), discrete Fourier transform (DFT) and empirical mode decomposition (EMD) are two main tools. They both can easily decompose any source signal into different components. DFT is based on Cosine functions;EMD is based on a collection of intrinsic mode functions (IMFs). With the help of Cosine functions and IMFs respectively, DFT and EMD can extract additional information from sensed signals. However, due to a considerably finite frequency resolution, EMD easily causes frequency mixing. Although DFT has a larger frequency resolution than EMD, its resolution is also finite. To effectively detect and capture hidden waveforms, we use an optimization algorithm, differential evolution (DE), to decompose. The technique is called SD by DE (SDDE). In contrast, SDDE has an infinite frequency resolution, and hence it has the opportunity to exactly decompose. Our proposed SDDE approach is the first tool of directly applying an optimization algorithm to signal decomposition in which the main components of source signals can be determined. For source signals from four combinations of three periodic waves, our experimental results in the absence of noise show that the proposed SDDE approach can exactly or almost exactly determine their corresponding separate components. Even in the presence of white noise, our proposed SDDE approach is still able to determine the main components. However, DFT usually generates spurious main components;EMD cannot decompose well and is easily affected by white noise. According to the superior experimental performance, our proposed SDDE approach can be widely used in the future to explore various signals for more valuable information.
A wideband butterfly antenna based on deep learning parameter optimization algorithm is proposed in this paper. Two neural networks are designed to model the mapping relationship of structure parameters to frequency r...
详细信息
ISBN:
(纸本)9781728181813
A wideband butterfly antenna based on deep learning parameter optimization algorithm is proposed in this paper. Two neural networks are designed to model the mapping relationship of structure parameters to frequency response and frequency response to structure parameters respectively. The parameter optimization algorithm proposed consists of two stages: training NN1 and optimizing parameters using NN2. A wideband butterfly antenna is designed to verify the algorithm. The experiment shows that the structure parameter optimization algorithm proposed can quickly optimize the structure parameters of antenna with the best preformance and save a lot of manpower and time cost.
This paper presents a new algorithm for optimizing parameters in swarm algorithm using reinforcement learning. The algorithm, called iSOMA-RL, is based on the iSOMA algorithm, a population-based optimization algorithm...
详细信息
This paper presents a new algorithm for optimizing parameters in swarm algorithm using reinforcement learning. The algorithm, called iSOMA-RL, is based on the iSOMA algorithm, a population-based optimization algorithm that mimics the competition-cooperation behavior of creatures to find the optimal solution. By using reinforcement learning, iSOMA-RL can dynamically and continuously optimize parameters, which can play a crucial role in determining the performance of the algorithm but are often difficult to determine. The reinforcement learning technique used is the state -of -the -art Proximal Policy optimization (PPO), which has been successful in many areas. The algorithm was compared to the original iSOMA algorithm and other algorithms from the SOMA family, showing better performance with only constant increase in computational complexity depending on number of function evaluations. Also we examine different sets of parameters to optimize and different reward functions. We also did comparison to widely used and state -of -the -art algorithms to illustrate improvement in performance over the original iSOMA algorithm.
暂无评论