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1268 results about "Data prediction" patented technology

In Data Mining, the term “Prediction” refers to calculated assumptions of certain turns of events made on the basis of available processed data. It is a cornerstone of predictive analytics. The prediction itself is calculated from the available data and modeled in accordance with the existing dynamics.

Data-driven lithium ion battery cycle life prediction method based on AR (Autoregressive) model and RPF (Regularized Particle Filtering) algorithm

A data-driven lithium ion battery cycle life prediction method based on an AR (Autoregressive) model and an RPF (Regularized Particle Filtering) algorithm relates to a lithium ion battery cycle life prediction method and belongs to the technical field of data prediction. The invention solves the problems in the existing lithium ion battery cycle life prediction method that the model-based prediction method is complicated in modeling, and parameters are difficult to identify. The data-driven lithium ion battery cycle life prediction method combines time sequence analysis with particle filter method and comprises the following steps: the AR model is firstly utilized to realize the multi-step prediction on battery performance degradation process time sequence data; and then, aiming at the problem of uncertainty expression of the cycle life prediction result, the regularized particle filtering method is introduced, and a lithium ion battery cycle life prediction method framework is proposed. The method proposed by the invention can be used for effectively predicating the cycle life of a lithium ion battery and realizes the output of probability density distribution of the predication result, has good computational efficiency and uncertainty expression ability.
Owner:HARBIN INST OF TECH

Visual analyzing and predicting method based on a virtual geological model

InactiveCN101515372ARealize the integrated rendering of time and spaceIncrease spaceSpecial data processing applications3D-image renderingSpatial analysisMulti dimensional
A visual analyzing and predicting method based on a virtual geological model is finished by depending on an interactive visual tool. The method mainly comprises steps of searching a multi-dimensional geological data model from a database and a file system; arranging or resetting a virtual geological scene by setting or regulating corresponding parameters and models; regulating coordinate, scale, data format and the like, of the geological model; sending results of visual calculating, analyzing, predicting and searching into a dual-display cache region; and integrally displaying geological data in a visual platform at real time. The method meets requirements of earth science application, enhances representability of geological data, improves comprehension and application environment of geological data, converts logical thinking of geologists into a trial ground having an imagery thinking of time and space in a virtual environment, helps strengthen deep recognition to complex geological phenomena, uncovers deep information and internal relation in geological data, digs out and extract knowledge unable to be obtained in a traditional mode, improves utilization rate and geospatial analytics of information, and provides a brand-new method for geologists to observe, explain, analyze and imitate geological phenomena in a three-dimensional space, predict and know geospatial distribution of geological structure in a studied area through known data, and obtain mine position, mine reserves and other important information. Furthermore, the human-computer interactive tool is simple and easy to learn to operate, saves cost, reduces blindness in application, reduces risk, conducts and makes decision for production and environment analysis and has significant economic and social benefits.
Owner:BEIJING INSTITUTE OF PETROCHEMICAL TECHNOLOGY +1

Auto-expanding/shrinking cost-optimized content distribution service method based on hybrid cloud scheduling model

The invention belongs to the technical field of cloud computing and network multimedia, and particularly provides an auto-expanding/shrinking cost-optimized content distribution service method based on a hybrid cloud scheduling model. The method comprises: a future number of user visits is predicted on the basis of historical data and provides basis for auto-expanding/shrinking of resources; according to the predicted value and a long-term scheduling algorithm, a rough plan of resource booking strategy is obtained through calculation; wherein a short-term scheduling model is introduced to reduce the prediction error and to improve the precision of resource supply and the quality of service. In the long-term scheduling algorithm, a locality-aware booking model is set up to derive the locality-aware resource booking algorithm. A resource prediction algorithm employs the ARIMA model. In a short-term adjustment algorithm, virtual machine status parameters are designed and a content missing algorithm is provided, so that the user experience of the entire system is further improved. The method enables hybrid cloud technology to support streaming media content distribution applications efficiently with auto-expanding/shrinking functions and optimized costs.
Owner:FUDAN UNIV

System for forecasting traffic flow of urban ring-shaped roads

The invention discloses a system for forecasting traffic flow of urban ring-shaped roads, relating the related technical fields of database management, data analysis and processing and data speculation. The system comprises a traffic flow data management system, a traffic flow data characteristic analysis system and a traffic flow data speculation system. The traffic flow data management system is used for maintaining the traffic flow database, realizing reading of real-time traffic flow data and input of predicted data; the traffic flow data characteristic analysis system is used for realizing characteristic analysis of traffic flow data and pre-processing traffic flow data; the traffic flow data speculation system is used for selecting traffic flow prediction models and analyzing predicting outcomes, realizing prediction method comparison and display and saving of the predicting outcomes. The system can solve the quality problem of traffic flow data and deviated prediction in the traditional traffic flow prediction, introduces various influencing factors of upper sections and lower sections of roads for predicting road traffic flow and realize real-time and accurate traffic flow prediction of the road network.
Owner:UNIV OF SCI & TECH BEIJING

User electricity consumption relevant factor identification and electricity consumption quantity prediction method under environment of big data

The invention provides a user electricity consumption relevant factor identification and electricity consumption quantity prediction method under the environment of big data. Multiple electricity consumption modes of users are mined and existing electricity consumption behavior analysis methods are expanded by applying a mass user electricity consumption characteristic subspace clustering analysis method based on the research of the user electricity consumption characteristic evaluation index by aiming at the characteristics that the big data relevant to electricity consumption quantity prediction are various, large in size, high in dimension and high in generation speed. Meanwhile, group division is performed on the users according to different electricity consumption modes, factors relevant to user group electricity consumption quantity are identified from the aspects of regional and industry economic data, weather conditions and electricity price by utilizing mutual information matrixes, and an electricity consumption quantity big data prediction model based on a random forest algorithm is constructed so that data driving of the whole process of electricity consumption prediction is realized, adverse influence on electricity consumption quantity prediction caused by difference of the electricity consumption modes can be avoided, and thus the method has relatively high prediction precision and is suitable for big data analysis and processing.
Owner:SHANGHAI JIAO TONG UNIV +1

Cloud computing resource pre-distribution achievement method

The invention provides a cloud computing resource pre-distribution achievement method. The cloud computing resource pre-distribution achievement method detailedly analyzes design and realization of a model, helps an information technology (IT) administrator to beforehand deploy various virtual machines to satisfy unexpected requests by forecasting possible user requests, and meanwhile forecasts possible physical resource demands aiming at specific resource types so as to beforehand purchase corresponding resources. The cloud computing resource pre-distribution achievement method comprises data collection; data washing, filtering requests of users, wherein the number of times of the requests is smaller than a preset number of times; model training, building a combined forecast model based on an array of time and types of the virtual machines, and then continuously leading in washed data and carrying out the model training according to a time window until the time window is filled, and accomplishing model convergence; data forecast, forecasting resource requests of a preset time based on the trained combined forecast model; and result processing, wherein under the premise of a preset forecast time, forecast results comprise total required quantity of each type of virtual machines, required quantity of the virtual machines in the next circle, and required quantity of a specific physical resource.
Owner:CSG EHV POWER TRANSMISSION +1

Method for predicting data and equipment

The invention provides a method for predicting data and an equipment. The method comprises the following steps of: reading a plurality of first data related to a first period which contains a plurality of first sub periods, wherein a plurality of first data and a plurality of first sub periods are in a one-to-one correspondence relationship; based on a plurality of first data and a plurality of first sub periods, determining a plurality of first trend values which are in a one-to-one correspondence relationship with a plurality of first sub periods; based on a plurality of first data and a plurality of first trend values, obtaining a compensation sequence constituted by a plurality of compensation amount, wherein a plurality of compensation amount and a plurality of first sub periods are in a one-to-one correspondence relationship; based on the compensation sequence, obtaining estimation values of the compensation dosage which corresponds to a second period by utilizing a support vector machine, wherein the time of the second period is later than that of the first period; based on the estimation values of compensation amount, predicting a second data related to the second period. The embodiment of the invention has effective prediction, thereby being capable of bringing considerable economic benefits for operators.
Owner:HUAWEI TECH CO LTD
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