The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Under real and continuously improving manufacturing conditions, lithography hotspot detection faces several key challenges. First, real hotspots become less but harder to fix at post-layout stages; second, false alarm rate must be kept low to avoid excessive and expensive post-processing hotspot removal; third, full chip physical verification and optimization require fast turn-around time. To address...
The importance of providing guaranteed Quality of Service (QoS) cannot be overemphasised, especially in the NGN environment which supports converged services on a common IP transport network. Call Admission Control (CAC) mechanisms do provide QoS to class-based services in a proactive manner. However, due to the factors of complexity, scale and dynamicity of NGN, Machine Learning techniques are favoured...
Ensemble methods represent an approach to combine a set of models, each capable of solving a given task, but which together produce a composite global model whose accuracy and robustness exceeds that of the individual models. Ensembles of neural networks have traditionally been applied to machine learning and pattern recognition but more recently have been applied to forecasting of time series data...
This paper applies DEA model to a sample of 58 power plate listed companies in the securities market in China in 2008, with a view to identifying the financial risk companies and non-financial risk companies, instead of using ST in the past. Then, after comparing logit regression model and neural network LVQ in predicting the company financial risks, the conclusion was drawn that neural network LVQ...
Based on the neural network theory, this paper proposes the neural network model to solve the surrounding rock displacement prediction of nonlinear problems. This model combines the advantages of wavelet time-frequency analysis and neural network self-learning. The studies had shown that the wavelet neural network had higher prediction accuracy. In addition, it could better reveal the changes of displacement...
An artificial neural network model forecasting diameter distribution of stands was created by using artificial neural network modeling technology, in Masson pine planted forest. Through training and optimum seeking, the idea model was created, in which the model structure is 3:6:6:1, the training error is 0.000281, and the total fitting accuracy is 98%. Concretely, the mean frequency fitting accuracy...
Online auctions have become extremely popular in recent years. Ability to predict winning bid prices accurately can help bidders to maximize their profit. This paper proposes a number of strategies and algorithms for performing such predictions for the first price sealed bid reverse auctions (FPSBRA). The neural networks (NN) and genetic programming (GP) learning techniques are used in the models...
Computer manufacturers spend a huge amount of time, resources, and money in designing new systems and newer configurations, and their ability to reduce costs, charge competitive prices, and gain market share depends on how good these systems perform. In this work, we concentrate on both the system design and the architectural design processes for parallel computers and develop methods to expedite...
TCP remains the protocol of choice for bulk data transfers over the Internet. A range of mathematical approaches were proposed to evaluate the performance of TCP, approaches validated through synthetic or endpoint controlled traffic, typically unsuitable for short-lived transfers or clients with unknown behaviour. This paper aims to overcome these problems by using a supervised adaptive learning approach...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.