A novel algorithmic scheme for numerical solution of the 3D Poisson-Nernst-Planck model is proposed. The algorithmic improvements are universal and independent of the detailed physical model. They include three major ...
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A novel algorithmic scheme for numerical solution of the 3D Poisson-Nernst-Planck model is proposed. The algorithmic improvements are universal and independent of the detailed physical model. They include three major steps: an adjustable gradient-based step value, an adjustable relaxation coefficient, and an optimized segmentation of the modeled space. The enhanced algorithm significantly accelerates the speed of computation and reduces the computational demands. The theoretical model was tested on a regular artificial channel and validated on a real protein channel-alpha-hemolysin, proving its efficiency. (C) 2008 Wiley Periodicals, Inc.
Analyzing and understanding emotional expressions in user comments is a crucial and complex task in business. Conducting text sentiment analysis is of great significance. This paper constructs a novel DIBTBL model tha...
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Analyzing and understanding emotional expressions in user comments is a crucial and complex task in business. Conducting text sentiment analysis is of great significance. This paper constructs a novel DIBTBL model that integrates an extended sentiment dictionary, an improved swarm intelligence algorithm, and deep learning techniques to accurately capture and analyze user emotions. Firstly, this paper expands the sentiment dictionary to extract emotion feature words from the review text. Secondly, the BERT model embeds these emotional feature words and pre-processed text into high-dimensional semantic space to obtain richer semantic representations and improve sentiment classification performance. Then, the TextCNN-BiLSTM feature extraction model is established to balance the grasping ability of local and global features. Fourthly, this paper innovatively improves the swarm intelligence algorithm BWO to optimize the parameters of the TextCNN-BiLSTM. Finally, MLP is employed for sentiment classification. The experimental data is crawled from Ctrip, China's largest hotel booking website. In the comparative experiment, the proposed model achieves a higher accuracy than TBL, DTBL, BTBL, and IBTBL by 2.94%, 2.44%, 1.64%, and 0.66%, respectively. In addition, we compare the proposed model with seven advanced models in the open dataset waimai_10k. The experimental results indicate that this model outperforms all the other models, with an average improvement in accuracy of 8.21%. The study offers precise insights into user sentiment, assisting companies in better understanding and meeting customer needs.
Mining co -location patterns hidden in spatial data is crucial for spatial association discovery, and it has broad prospects in many applications. H igh U tility C o -location P attern M ining (HUCPM) further takes th...
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Mining co -location patterns hidden in spatial data is crucial for spatial association discovery, and it has broad prospects in many applications. H igh U tility C o -location P attern M ining (HUCPM) further takes the utility factor of spatial features into consideration, so it is more realistic compared with the traditional co -location pattern mining. However, HUCPM is more difficult, since the Apriori-like pruning technique does not apply. To address this problem, we firstly suggest two novel pruning strategies to trim the pattern search space. Then, a series of optimizing techniques are presented to speed up the pattern utility ratio calculation of each candidate. Based on above techniques, a fast HUCPM algorithm is proposed, which searches for high utility colocations involved in each pattern branch via a depth -extending manner and equips with a heuristic strategy to enhance the effect of pruning techniques. Moreover, we theoretically prove the completeness and correctness of the proposed algorithm, and discuss its algorithmic complexity. On multiple spatial datasets, we conduct substantial experiments to reveal the superiority of our algorithm in efficiency and scalability, as well as the effectiveness of the proposed technique. Particularly, the proposed algorithm in this paper runs faster than other baselines for several times to several orders of magnitude.
The connection of high penetrations of renewable generation such as wind to distribution networks requires new active management techniques. Curtailing distributed generation during periods of network congestion allow...
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The connection of high penetrations of renewable generation such as wind to distribution networks requires new active management techniques. Curtailing distributed generation during periods of network congestion allows for a higher penetration of distributed wind to connect, however, it reduces the potential revenue from these wind turbines. Energy storage can be used to alleviate this and the store can also be used to carry out other tasks such as trading on an electricity spot market, a mode of operation known as arbitrage. The combination of available revenue streams is crucial in the financial viability of energy storage. This study presents a heuristic algorithm for the optimisation of revenue generated by an energy storage unit working with two revenue streams: generation-curtailment reduction and arbitrage. The algorithm is used to demonstrate the ability of storage to generate revenue and to reduce generation curtailment for two case study networks. Studies carried out include a single wind farm and multiple wind farms connected under a 'last-in-first-out' principle of access. The results clearly show that storage using both operating modes increases revenue over either mode individually. Moreover, energy storage is shown to be effective at reducing curtailment while increasing the utilisation of circuits linking the distribution and transmission networks. Finally, renewable subsidies are considered as a potential third revenue stream. It is interesting to note that under current market agreements such subsidies have the potential to perversely encourage the installation of inefficient storage technologies, because of increased losses facilitating greater "utilisation" of renewable generation.
With the continuous development of science and technology, the information age has arrived, and people have fully entered the information age. In this new era, Internet technology has achieved unprecedented developmen...
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With the continuous development of science and technology, the information age has arrived, and people have fully entered the information age. In this new era, Internet technology has achieved unprecedented development, and many innovative technologies have also been proposed. The competition in the logistics industry is becoming more and more fierce. Someone proposed the concept of intelligent logistics. This concept has been continuously expanded and the requirements have become higher and higher. Finally, an intelligent logistics management supported by the Internet of Things technology has emerged. technology. In our school's research, we mainly proposed an intelligent distribution model based on the Internet of Things. This model not only optimizes the distribution process, but also proposes an efficient distribution strategy when faced with a large amount of data. This technology mainly uses the information interaction technology in the Internet of Things, which can ensure that the average delivery speed is the fastest, the average transportation distance is the shortest, and the time consumed in the logistics transmission process is the shortest. In the decision-making process of this intelligent distribution model, we must first establish some intelligent distribution models controlled by multiple indicators. During the experiment, we built a logistics perception system and used heuristic algorithms to solve the packing problem. Answered. The mainstream solution algorithm we use genetic algorithm, a large number of experiments and data show that this algorithm is scientifically based, and it has also exerted its due effect in application. This article mainly analyzes the impact of the intelligent logistics system provided by the Internet of Things technology, and then looks forward to the future development trend of the system. We hope that through the analysis of the status quo, we can promote the further development of my country's Internet of Things techn
The modified autocorrelation algorithm for synchronizing orthogonal frequency-division multiplexing signals propagating over acoustic underwater communications systems is examined, and analytical estimates of its accu...
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The modified autocorrelation algorithm for synchronizing orthogonal frequency-division multiplexing signals propagating over acoustic underwater communications systems is examined, and analytical estimates of its accuracy are presented. It is demonstrated that the algorithm optimization under multipath channel conditions leads to modified window functions used to calculate likelihood functions. The suboptimal efficient variant of the algorithm based on rectangular windows is proposed.
The optimization of traditional FTL(Flash Translation Layer) algorithm is mainly aimed at the average response time of flash memory read and write operation on a flash chip, because of the Out-of-place update, traditi...
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The optimization of traditional FTL(Flash Translation Layer) algorithm is mainly aimed at the average response time of flash memory read and write operation on a flash chip, because of the Out-of-place update, traditional FTL algorithm writes data in a new free page each time, and a new block is assigned when a block is full. Therefore, when the flash memory is almost full, a written request will lead to a garbage collection, in which there will be many write copies, which will lead to a significant decrease in response time. In this paper, we optimize the traditional FTL algorithm and propose an FTL algorithm that guarantees real-time performance by shortening the worst response time of the request as a measure of the guaranteed flash Qos (Quality of Service) under the condition that the address mapping is provided the upper layer. The algorithm adopts the idea of space-for-time and spreads the written copy of flash memory to each write request so that the worst response time of the write request is significantly reduced. The algorithm also wears balancing considerations to the algorithm. After experimental verification, the proposed algorithm has advantages over existing FTL algorithms in terms of real-time performance and has a performance improvement of more than 11% in terms of average response time and wear balance. By the way, we add the wear-level module into an algorithm. According to improving the algorithm, the worst response time has shorten 47.6%.
To study the application of ZigBee protocol in the security algorithm of Internet of Things, the relevant development status at home and abroad is firstly summarized and ZigBee technology is introduced in detail. Then...
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To study the application of ZigBee protocol in the security algorithm of Internet of Things, the relevant development status at home and abroad is firstly summarized and ZigBee technology is introduced in detail. Then, the principle of AES-128 algorithm is analyzed, and the steps of decryption algorithm are adjusted, so that the decryption algorithm is symmetric in structure and encryption algorithm. In addition, the encryption and decryption algorithm of AES-128 is implemented by using C language. Based on the characteristics of simplicity and low cost of ZigBee technology, the two optimizationalgorithms are designed and implemented from the analysis of simplicity and efficiency based on the performances of security algorithm. The analysis and test results show that the two optimizationalgorithms are better than the UN optimized algorithm in terms of speed and complexity. To sum up, in the result comparison, it is found that the speed and complexity of the round operation optimizationalgorithm is better than that of the column obfuscation optimizationalgorithm.
Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental ***,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(M...
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Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental ***,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(MUSIC)and compressed sensing,etc.,cannot achieve both low complexity and high resolution *** paper proposes an efficient 2-D MUSIC algorithm for super-resolution target estimation/tracking based on FMCW ***,we enhance the efficiency of 2-D MUSIC azimuth-range spectrum estimation by incorporating 2-D DFT and multi-level resolution searching ***,we apply the gradient descent method to tightly integrate the spatial continuity of object motion into spectrum estimation when processing multi-epoch radar data,which improves the efficiency of continuous target *** two approaches have improved the algorithm efficiency by nearly 2-4 orders of magnitude without losing accuracy and *** experiments are conducted to validate the effectiveness of the algorithm in both single-epoch estimation and multi-epoch tracking scenarios.
作者:
Zhang, JieJinan Univ
Sch Mech & Construct Engn MOE Key Lab Disaster Forecast & Control Engn Guangzhou 510632 Peoples R China
This paper presents a comprehensive study of the second-order-type time integration methods family encompassing the linear multistep (LMS) methods, the single-step methods, and the LMS equivalent single-step methods f...
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This paper presents a comprehensive study of the second-order-type time integration methods family encompassing the linear multistep (LMS) methods, the single-step methods, and the LMS equivalent single-step methods for structural dynamics. An analytical accuracy framework for algorithm design, convergence, and optimization is developed, where the obstacles encountered in algorithms construction, convergence accuracy, algorithms equivalence, accuracy measurement, and accuracy optimization in traditional accuracy frameworks are well addressed. Rigorous accuracy analysis successively to the second-order-type LMS (LMS2) methods, the single-step methods, and the LMS2 equivalent single-step methods aims to reveal optimal algorithms with desirable numerical properties. First, independent implicit algorithms including the velocity type and the acceleration type LMS2 methods except the displacement type ones are newly revealed in the LMS2 methods family with second-order convergence and A-stability, and three error constants that can play essential roles in the accuracy measurement and algorithm optimization are developed. Second, a single-step methods family where the displacement, velocity, and acceleration can achieve the same order of accuracy simultaneously is revealed in a generalized 16 -parameters methods family, which contains numerous conventional single-step single-solve methods as subfamily methods. It is found that the unit consistent and non-consistent represen-tations show a significant difference in the local truncation error, stability, and convergence performances. Third, a family of accuracy-improved single-step methods with algorithmic equivalence, which is stricter than the traditional spectral equivalence, to the LMS2 methods is revealed. It is clarified that the difference between the methods with equivalence can significantly influence their convergence accuracy, and the error constants concept of the LMS2 methods can be extended to the single-step m
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