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检索条件"主题词=Prediction algorithms"

共 30476 条记录，以下是31-40 订阅

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Low complexity MAD prediction algorithms for rate controllable H.264/AVC hardware encoders

Low complexity MAD prediction algorithms for rate controllab...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Li-Chuan Chang Chih-Hung Kuo Bin-Da Liu Department of Electrical Engineering National Cheng Kung University Tainan Taiwan

This paper presents two low complexity macroblock-level MAD (Mean Absolute Difference) prediction algorithms for H.264/AVC rate control. Both of the algorithms consider the rate-distortion performance and its hardware cost jointly. One of the algorithms predicts the MAD value by observing the motion vector of the surrounding macroblocks (MB), the other one uses numerical analysis to find the best fit weighting factors for the MAD value. These algorithms do not suffer from the MB-pipeline problems which decrease the rate-distortion performance, thus they are suitable for H.264/AVC hardware encoders. Experimental results show that the proposed MAD prediction algorithm can further improve the rate-distortion performance for the rate control scheme. Compared with the JVT-G012 rate control scheme, our algorithms can increase the PSNR to 0.38 dB and 0.35 dB, respectively.

关键词： prediction algorithms Automatic voltage control Hardware Rate-distortion Quadratic programming Quantization Videoconference Motion compensation Predictive models Embedded system

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Evolutionary self-adaptive multimodel prediction algorithms of the fetal magnetocardiogram

Evolutionary self-adaptive multimodel prediction algorithms ...

引用

International Conference on Digital Signal Processing (DSP)

作者： A.V. Adamopoulos P.A. Anninos S.D. Likothanassis G.N. Beligiannis L.V. Skarlas E.N. Demiris D. Papadopoulos Department of Computer Engineering and Informatics Laboratory of Pattern Recognition University of Patras Patras Greece Department of Medicine Medical Physics Laboratory Democritus University of Thrace Alexandroupolis Greece Computer Technology Institute Patras Greece

A novel technique for the analysis, nonlinear model identification and prediction of the fetal magnetocardiogram (f-MCG) is presented. f-MCGs can be recorded with the use of specific totally non-invasive superconductive quantum interference devices (SQUID). For the analysis and classification of the f-MCG signals we introduce an intelligent method that combines the following well known advanced signal processing techniques: the genetic algorithms (GA), the multimodel partitioning (MMP) theory and the extended Kalman filters (EKF). Simulations illustrate that the proposed method is selecting the correct model structure and identifies the model parameters in a sufficiently small number of iterations and tracks successfully changes in the signal, in real time. The information provided by the proposed analysis is easily interpreted and assessed by gynecologists and consist of the clinical status of the fetus. The proposed algorithm can be parallel implemented and also a VLSI implementation is feasible.

关键词： prediction algorithms Signal processing algorithms Superconducting magnets Magnetic analysis Signal processing Predictive models Magnetic devices Superconductivity Interference SQUIDs

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A comparative Analyis of House Price prediction algorithms

A comparative Analyis of House Price Prediction Algorithms

引用

International Conference for Convergence of Technology (I2CT)

作者： Rahul Chauhan Tushar Sharma Ruchira Rawat Rudresh Pillai Kanegonda Ravi Chythanya Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computer Science & Artificial Intelligence SR University Warangal India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

This paper aims to present the implementation of two machine learning algorithms, Linear Regression and Lasso Regression for the task of predicting the price of the house located in the city of Bengaluru, India. The task of predicting house price accurately is quite difficult as it depends on a lot of factors, and needs of the buyer. For predicting these prices, we can try to create datasets which contains details of the factors that people look for while buying Houses such as size, location, bathroom etc. To analyses the data, we can usecertain algorithms such as linear regression, lasso regression etc. By using algorithms like this, we can reduce the margin of error of our model and try to make it more accurate and usable. Such models can be used by real estate agents,sellers as well as the people who want to buy house to get the best deal for them. In future,researcher can also integrate models like this with the real estate's websites like MagicBricks,99Acres to give better and more accurate recommendations to people.

关键词： Analytical models Machine learning algorithms Linear regression Urban areas Predictive models prediction algorithms Data models

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Structural prediction algorithms

Structural Prediction Algorithms

引用

International Conference on Management of Large-Scale System Development (MLSD)

作者： D. Bordukov Dorofeyuk Yu V.A. Trapeznikov Institute of Control Sciences RAS Moscow Russia

A structural approach to the forecasting problem is considered. The idea of this approach is that for each object of the system under study it is necessary to forecast only its belonging to a certain structural unit (class) within the framework of the selected structure of the considered set of objects. The description of the basic structural predicting algorithm is given. Then, additional constraints are introduced that must be satisfied by the structural prediction results. These limitations may arise from the physical properties of the objects in question or may be set by experts. New algorithms of structural forecasting are described taking into account constraints of different nature.

关键词： Standards Forecasting Classification algorithms prediction algorithms Trajectory Rails Physics

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A comparison of backward adaptive prediction algorithms in low delay speech coders

A comparison of backward adaptive prediction algorithms in l...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： J.D. Gibson Y.C. Cheong H.C. Woo W.-W. Chang Department of Electrical Engineering Texas A and M University College Station TX USA Department of Communication Engineering National Chiao Tung University Taiwan

Simulation results are presented comparing the performances of four backward adaptive lattice algorithms for updating the short-term predictors in adaptive predictive coding (APC) and differential pulse code modulation (DPCM) code generators for low-delay tree coding of speech at 16 and 9.6 kb/s. The algorithms studied are the least-squares lattice, the exponential window lattice, the signal-driven lattice, and the residual-driven lattice. Ideal channels are emphasized, and comparisons are based primarily upon frequency-weighted signal-to-noise ratio and subjective listening tests.< >

关键词： prediction algorithms Lattices Pulse modulation Predictive models Predictive coding Modulation coding Pulse generation Speech coding Frequency Signal to noise ratio

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Leveraging Race prediction algorithms to Enhance Team Composition in Big Data Science Teams

Leveraging Race Prediction Algorithms to Enhance Team Compos...

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IEEE International Conference on Big Data

作者： Thanathip Chumthong Kulsawasd Jitkajornwanich Obada Kraishan Kerk F. Kee Akan Narabin King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand Texas Tech University Lubbock TX USA

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

As big data science projects scale in complexity, optimizing team composition has become vital for improving creativity, productivity, and project success. We explore the possibility of incorporating race prediction algorithms for enhancing racial diversity in team composition in big data science projects. This paper evaluates five race prediction algorithms—wru, ethnicolr, ethnicolr2, pyethnicity, and rethnicity—and then discuss their potential in supporting racially diverse team assembly in big data projects. Utilizing three datasets, we assess algorithm performance and applicability, emphasizing their role in building balanced teams that enhance agility, inclusivity, and bias mitigation. We present an actionable methodology for integrating demographic insights into team management. In addition, we propose ethical safeguards to ensure responsible race prediction use, recommending data privacy measures, aggregate-only data handling, and transparency in communication. We argue that when used within ethical constraints, race prediction can support robust team processes, reduce reliance on less diverse teams, and ultimately facilitate more creative and equitable big data project outcomes.

关键词： Measurement Ethics Data privacy Companies Big Data Data science Predictive models prediction algorithms Assembly Monitoring

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Impact of the Inaccuracy of Distance prediction algorithms on Internet Applications - an Analytical and Comparative Study

Impact of the Inaccuracy of Distance Prediction Algorithms o...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： R. Zhang C. Tang Y. C. Hu S. Fahmy X. Lin School of Electrical and Computer Engineering Purdue University USA IBM Thomas J. Watson Research Center USA Watson Research Center IBM Thomas J. Watson Research Center USA Department of Computer Science Purdue University USA

Distance prediction algorithms use O(N) round trip time (RTT) measurements to predict the N 2 RTTs among N nodes. Distance prediction can be applied to improve the performance of a wide variety of Internet applications: for instance, to guide the selection of a download server from multiple replicas, or to guide the construction of overlay networks or multicast trees. Although the accuracy of existing prediction algorithms has been extensively compared using the relative prediction error metric, their impact on applications has not been systematically studied. In this paper, we consider distance prediction algorithms from an application's perspective to answer the following questions: (1) Are existing prediction algorithms adequate for the applications? (2) Is there a significant performance difference between the different prediction algorithms, and which is the best from the application perspective? (3) How does the prediction error propagate to affect the user perceived application performance? (4) How can we address the fundamental limitation (i.e., inaccuracy) of distance prediction algorithms? We systematically experiment with three types of representative applications (overlay multicast, server selection, and overlay construction), three distance prediction algorithms (GNP, IDES, and the triangulated heuristic), and three real-world distance datasets (King, PlanetLab, and AMP). We find that, although using prediction can improve the performance of these applications, the achieved performance can be dramatically worse than the optimal case where the real distances are known. We formulate statistical models to explain this performance gap. In addition, we explore various techniques to improve the prediction accuracy and the performance of prediction-based applications. We find that selectively conducting a small number of measurements based on prediction-based screening is most effective.

关键词： prediction algorithms Internet Algorithm design and analysis Multicast algorithms Extraterrestrial measurements Accuracy Time measurement IP networks Network servers Web server

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Power quality prediction algorithms and analysis

Power quality prediction algorithms and analysis

引用

International Conference on System Science and Engineering (ICSSE)

作者： Gao Xin Dai Shengkui College of Electrical and Information Engineering Anhui University of Science And Technology HuaiNan China Guotou Xinji Energy Co. HuaiNan China

By using the gray prediction adaptive system whose parameter is variable and structure is fixed, this paper revises data sequence of the distortion in the power by using improved model. This method also increases pred... 详细信息

关键词： Predictive models Data models Mathematical model prediction algorithms Adaptation models Accuracy Algorithm design and analysis

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Benchmarking Explicit Rating prediction algorithms for Cosmetic Products

Benchmarking Explicit Rating Prediction Algorithms for Cosme...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Raditya Nurfadillah Fariz Darari Radityo Eko Prasojo Yasmin Amalia Faculty of Computer Science Universitas Indonesia Depok Indonesia Tokopedia-UI AI Center of Excellence Depok Indonesia Kata.ai Jakarta Indonesia

ISBN: (数字)9781728184067

ISBN: (纸本)9781728184074

Recommendation systems have become a staple feature for any e-commerce sites. The ability to predict whether a customer likes an unseen product forms the very foundation of a recommendation system. In this paper, we concern the issue of explicit rating prediction over cosmetic products. Given a dataset of cosmetic product ratings, we analyze the characteristics of the dataset and implement a wide range of algorithms, such as KNN and matrix factorization, to predict such ratings. We evaluate the performance of these algorithms using MAE and RMSE measures, and discuss factors that may contribute to their performance results. Our experiments have shown that the SVD++ technique performs the best among all with an MAE of 0.7699 and an RMSE of 0.9696. We hope that our paper can shed new light on the selection of explicit rating prediction algorithms not only in the domain of beauty products, but also in wider scenarios.

关键词： prediction algorithms Measurement Recommender systems Singular value decomposition Seminars Privacy Matrix decomposition

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Efficient search and mode prediction algorithms for motion estimation in H.264/AVC

Efficient search and mode prediction algorithms for motion e...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Gwo-Long Li Mei-Juan Chen Hung-Ju Li Ching-Ting Hsu Department of Electrical Engineering National Dong Hwa University Hualien Taiwan

ISBN: (纸本)0780388348

The H.264 video coding standard adopts different coding schemes like variable block sizes and multiple reference frames for motion estimation. Hence, H.264/AVC provides gains in compression efficiency of up to 50% over a wide range of bit rates and video resolutions compared to previous standards. However, these features incur a considerable increase in encoder complexity, mainly with regards to motion estimation and mode decision. In this paper, efficient methods aimed at speed up of motion estimation and mode decision are proposed. Experimental results show that our proposed algorithms can save a coding time of about 88% compared with the reference software JM80 while keeping the video quality.

关键词： prediction algorithms Motion estimation Automatic voltage control Video compression Image coding Video coding Bit rate Software algorithms Software quality Image quality

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