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Application of Predictive Algorithm in Head-Tracking System
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作者 姜明 李科杰 李鑫 《Journal of Beijing Institute of Technology》 EI CAS 2002年第3期306-310,共5页
The worldwide research status of head tracking is introduced and the works made in the research of the predictive algorithm and in the exploration of the rule of the head tracking are set forth. A time delay model f... The worldwide research status of head tracking is introduced and the works made in the research of the predictive algorithm and in the exploration of the rule of the head tracking are set forth. A time delay model for the telerobotic scout system is built. In respect of eliminating error caused by time delay and making reasonable prediction to the data stream, many methods are experimented in order to realize the aim of real time tracking. The application of extrapolation algorithm and auto recursive algorithm in the orientation tracking is described in detail. These two algorithms are realized in Matlab environment. Through analysis of the curves generated by using these two predictive algorithms, an appropriate method was applied in the telerobotic scout system. The effect is satisfying. 展开更多
关键词 TELEOPERATION head tracking predictive algorithm
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Nonlinear model predictive control based on support vector machine and genetic algorithm 被引量:5
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作者 冯凯 卢建刚 陈金水 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第12期2048-2052,共5页
This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used ... This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection. 展开更多
关键词 Support vector machine Genetic algorithm Nonlinear model predictive control Neural network Modeling
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Employment of predictive search algorithm in digital image correlation
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作者 马志峰 王昊 韩福海 《Journal of Beijing Institute of Technology》 EI CAS 2014年第2期254-259,共6页
A predictive search algorithm to estimate the size and direction of displacement vectors was presented.The algorithm decreased the time of calculating the displacement of each pixel.In addition,the updating reference ... A predictive search algorithm to estimate the size and direction of displacement vectors was presented.The algorithm decreased the time of calculating the displacement of each pixel.In addition,the updating reference image scheme was used to update the reference image and to decrease the computation time when the displacement was larger than a certain number.In this way,the search range and computational complexity were cut down,and less EMS memory was occupied.The capability of proposed search algorithm was then verified by the results of both computer simulation and experiments.The results showed that the algorithm could improve the efficiency of correlation method and satisfy the accuracy requirement for practical displacement measuring. 展开更多
关键词 machine vision predictive search algorithm digital image correlation sub-pixel displacement measurement
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Development,validation,and transportability of several machine-learned,non-exercise-based VO_(2max)prediction models for older adults
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作者 Benjamin T.Schumacher Michael J.LaMonte +5 位作者 Andrea Z.LaCroix Eleanor M.Simonsick Steven P.Hooker Humberto Parada Jr. John Bellettiere Arun Kumar 《Journal of Sport and Health Science》 SCIE CAS CSCD 2024年第5期611-620,共10页
Background:There exist few maximal oxygen uptake(VO_(2max))non-exercise-based prediction equations,fewer using machine learning(ML),and none specifically for older adults.Since direct measurement of VO_(2max)is infeas... Background:There exist few maximal oxygen uptake(VO_(2max))non-exercise-based prediction equations,fewer using machine learning(ML),and none specifically for older adults.Since direct measurement of VO_(2max)is infeasible in large epidemiologic cohort studies,we sought to develop,validate,compare,and assess the transportability of several ML VO_(2max)prediction algorithms.Methods:The Baltimore Longitudinal Study of Aging(BLSA)participants with valid VO2_(max)tests were included(n=1080).Least absolute shrinkage and selection operator,linear-and tree-boosted extreme gradient boosting,random forest,and support vector machine(SVM)algorithms were trained to predict VO_(2max)values.We developed these algorithms for:(a)the overall BLSA,(b)by sex,(c)using all BLSA variables,and(d)variables common in aging cohorts.Finally,we quantified the associations between measured and predicted VO_(2max)and mortality.Results:The age was 69.0±10.4 years(mean±SD)and the measured VO_(2max)was 21.6±5.9 mL/kg/min.Least absolute shrinkage and selection operator,linear-and tree-boosted extreme gradient boosting,random forest,and support vector machine yielded root mean squared errors of 3.4 mL/kg/min,3.6 mL/kg/min,3.4 mL/kg/min,3.6 mL/kg/min,and 3.5 mL/kg/min,respectively.Incremental quartiles of measured VO_(2max)showed an inverse gradient in mortality risk.Predicted VO_(2max)variables yielded similar effect estimates but were not robust to adjustment.Conclusion:Measured VO_(2max)is a strong predictor of mortality.Using ML can improve the accuracy of prediction as compared to simpler approaches but estimates of association with mortality remain sensitive to adjustment.Future studies should seek to reproduce these results so that VO_(2max),an important vital sign,can be more broadly studied as a modifiable target for promoting functional resiliency and healthy aging. 展开更多
关键词 Cardiorespiratory fitness Prediction algorithms EPIDEMIOLOGY MORTALITY
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Carbon Emission Factors Prediction of Power Grid by Using Graph Attention Network
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作者 Xin Shen Jiahao Li +3 位作者 YujunYin Jianlin Tang Weibin Lin Mi Zhou 《Energy Engineering》 EI 2024年第7期1945-1961,共17页
Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice,which is of immense importance in mobilizing the entire society to reduce carbon emissions.The method of calcul... Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice,which is of immense importance in mobilizing the entire society to reduce carbon emissions.The method of calculating node carbon emission factors based on the carbon emissions flow theory requires real-time parameters of a power grid.Therefore,it cannot provide carbon factor information beforehand.To address this issue,a prediction model based on the graph attention network is proposed.The model uses a graph structure that is suitable for the topology of the power grid and designs a supervised network using the loads of the grid nodes and the corresponding carbon factor data.The network extracts features and transmits information more suitable for the power system and can flexibly adjust the equivalent topology,thereby increasing the diversity of the structure.Its input and output data are simple,without the power grid parameters.We demonstrated its effect by testing IEEE-39 bus and IEEE-118 bus systems with average error rates of 2.46%and 2.51%. 展开更多
关键词 Predict carbon factors graph attention network prediction algorithm power grid operating parameters
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Recovery and grade prediction of pilot plant flotation column concentrate by a hybrid neural genetic algorithm 被引量:6
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作者 F. Nakhaei M.R. Mosavi A. Sam 《International Journal of Mining Science and Technology》 SCIE EI 2013年第1期69-77,共9页
Today flotation column has become an acceptable means of froth flotation for a fairly broad range of applications, in particular the cleaning of sulfides. Even after having been used for several years in mineral proce... Today flotation column has become an acceptable means of froth flotation for a fairly broad range of applications, in particular the cleaning of sulfides. Even after having been used for several years in mineral processing plants, the full potential of the flotation column process is still not fully exploited. There is no prediction of process performance for the complete use of available control capabilities. The on-line estimation of grade usually requires a significant amount of work in maintenance and calibration of on-stream analyzers, in order to maintain good accuracy and high availability. These difficulties and the high cost of investment and maintenance of these devices have encouraged the approach of prediction of metal grade and recovery. In this paper, a new approach has been proposed for metallurgical performance prediction in flotation columns using Artificial Neural Network (ANN). Despite of the wide range of applications and flexibility of NNs, there is still no general framework or procedure through which the appropriate network for a specific task can be designed. Design and structural optimization of NNs is still strongly dependent upon the designer's experience. To mitigate this problem, a new method for the auto-design of NNs was used, based on Genetic Algorithm (GA). The new proposed method was evaluated by a case study in pilot plant flotation column at Sarcheshmeh copper plant. The chemical reagents dosage, froth height, air, wash water flow rates, gas holdup, Cu grade in the rougher feed, flotation column feed, column tail and final concentrate streams were used to the simulation by GANN. In this work, multi-layer NNs with Back Propagation (BP) algorithm with 8-17-10-2 and 8- 13-6-2 arrangements have been applied to predict the Cu and Mo grades and recoveries, respectively. The correlation coefficient (R) values for the testing sets for Cu and Mo grades were 0.93, 0.94 and for their recoveries were 0.93, 0.92, respectively. The results discussed in this paper indicate that the proposed model can be used to predict the Cu and Mo grades and recoveries with a reasonable error. 展开更多
关键词 Artificial neural network Genetic algorithm Flotation column Grade Recovery Prediction
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Failure Prediction and Intelligent Maintenance of a Transportation Company’s Urban Fleet
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作者 Crépin Foké Jean-Pierre Kenné Ngongang Somen Bill Diego 《Journal of Transportation Technologies》 2023年第1期1-17,共17页
The present work deals with intelligent vehicle fleet maintenance and prediction. We propose an approach based primarily on the history of failures data and on the geographical data system. The objective here is to pr... The present work deals with intelligent vehicle fleet maintenance and prediction. We propose an approach based primarily on the history of failures data and on the geographical data system. The objective here is to predict the date of failures for a fleet of vehicles in order to allow the maintenance department to efficiently deploy the proper resources;we further provide specific details regarding the origins of failures, and finally, give recommendations. This study used the Société de transport de Montréal (STM)’s historical bus failure data as well as weather data from Environment Canada. We thank Facebook’s Prophet, Simple Feed-forward, and Beats algorithms (Uber), we proposed a set of computer codes that allow us to identify the 20% of buses that are responsible for the 80% of failures by mean of the failure history. Then, we deepened our study on the unreliable equipments identified during the diffusion of our computer code This allowed us to propose probable predictions of the dates of future failures. To ensure the validity of the proposed algorithm, we carried out simulations with more than 250,000 data. The results obtained are similar to the predicted theoretical values. 展开更多
关键词 Maintenance 4.0 Digital Technologies Failureprediction Artificial Intelligence Artificial Intelligence Prediction algorithm
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Prediction-based protocol for mobile target tracking in wireless sensor networks 被引量:3
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作者 Liang Xue Zhixin Liu Xinping Guan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2011年第2期347-352,共6页
Remote tracking for mobile targets is one of the most important applications in wireless sensor networks (WSNs). A target tracking protoco–exponential distributed predictive tracking (EDPT) is proposed. To reduce... Remote tracking for mobile targets is one of the most important applications in wireless sensor networks (WSNs). A target tracking protoco–exponential distributed predictive tracking (EDPT) is proposed. To reduce energy waste and response time, an improved predictive algorithm–exponential smoothing predictive algorithm (ESPA) is presented. With the aid of an additive proportion and differential (PD) controller, ESPA decreases the system predictive delay effectively. As a recovery mechanism, an optimal searching radius (OSR) algorithm is applied to calculate the optimal radius of the recovery zone. The simulation results validate that the proposed EDPT protocol performes better in terms of track failed ratio, energy waste ratio and enlarged sensing nodes ratio, respectively. 展开更多
关键词 wireless sensor network target tracking protocol predictive algorithm recovery mechanism.
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A NEW TECHNIQUE FOR PREDICTING DISTRIBUTION OF TERRESTRIAL VERTEBRATES USING INFERENTIAL MODELING 被引量:2
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作者 陈国君 A.Townsend Peterson 《Zoological Research》 CAS CSCD 2000年第3期231-237,共7页
A new technique for predicting species' geographic distribution is described.The approach involves 3 steps:①setting up geographic base data;②collecting and georeferencing distributional points;③modeling ecologi... A new technique for predicting species' geographic distribution is described.The approach involves 3 steps:①setting up geographic base data;②collecting and georeferencing distributional points;③modeling ecological niches using the biodiversity species workshop implementation of the genetic algorithm for rule set prediction (GARP).To illustrate these procedures,an example based on the Brown Eared Pheasant (Crossoptilon mantchuricum) is developed.This technique constitutes a useful tool for assessing geographic distribution for questions of ecology,biogeography,systematics,and conservation biology. 展开更多
关键词 Geographic information systems Genetic algorithm for rule set prediction DISTRIBUTION Ecological niche
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Advances of Bioinformatics Tools Applied in Virus Epitopes Prediction 被引量:7
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作者 Simon Rayner 《Virologica Sinica》 SCIE CAS CSCD 2011年第1期1-7,共7页
In recent years,the in silico epitopes prediction tools have facilitated the progress of vaccines development significantly and many have been applied to predict epitopes in viruses successfully. Herein,a general over... In recent years,the in silico epitopes prediction tools have facilitated the progress of vaccines development significantly and many have been applied to predict epitopes in viruses successfully. Herein,a general overview of different tools currently available,including T cell and B cell epitopes prediction tools,is presented. And the principles of different prediction algorithms are reviewed briefly. Finally,several examples are present to illustrate the application of the prediction tools. 展开更多
关键词 EPITOPE BIOINFORMATICS Epitope prediction algorithms
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Ship motion extreme short time prediction of ship pitch based on diagonal recurrent neural network 被引量:3
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作者 SHEN Yan XIE Mei-ping 《Journal of Marine Science and Application》 2005年第2期56-60,共5页
A DRNN (diagonal recurrent neural network) and its RPE (recurrent prediction error) learning algorithm are proposed in this paper .Using of the simple structure of DRNN can reduce the capacity of calculation. The prin... A DRNN (diagonal recurrent neural network) and its RPE (recurrent prediction error) learning algorithm are proposed in this paper .Using of the simple structure of DRNN can reduce the capacity of calculation. The principle of RPE learning algorithm is to adjust weights along the direction of Gauss-Newton. Meanwhile, it is unnecessary to calculate the second local derivative and the inverse matrixes, whose unbiasedness is proved. With application to the extremely short time prediction of large ship pitch, satisfactory results are obtained. Prediction effect of this algorithm is compared with that of auto-regression and periodical diagram method, and comparison results show that the proposed algorithm is feasible. 展开更多
关键词 extreme short time prediction diagonal recursive neural network recurrent prediction error learning algorithm UNBIASEDNESS
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Performance prediction of gravity concentrator by using artificial neural network-a case study 被引量:3
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作者 Panda Lopamudra Tripathy Sunil Kumar 《International Journal of Mining Science and Technology》 SCIE EI 2014年第4期461-465,共5页
In conventional chromite beneficiation plant, huge quantity of chromite is used to loss in the form of tailing. For recovery these valuable mineral, a gravity concentrator viz. wet shaking table was used.Optimisation ... In conventional chromite beneficiation plant, huge quantity of chromite is used to loss in the form of tailing. For recovery these valuable mineral, a gravity concentrator viz. wet shaking table was used.Optimisation along with performance prediction of the unit operation is necessary for efficient recovery.So, in this present study, an artificial neural network(ANN) modeling approach was attempted for predicting the performance of wet shaking table in terms of grade(%) and recovery(%). A three layer feed forward neural network(3:3–11–2:2) was developed by varying the major operating parameters such as wash water flow rate(L/min), deck tilt angle(degree) and slurry feed rate(L/h). The predicted value obtained by the neural network model shows excellent agreement with the experimental values. 展开更多
关键词 Chromite Artificial neural network Wet shaking table Performance prediction Back propagation algorithm
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NONLINEAR MODELING AND CONTROLLING OF ARTIFICIAL MUSCLE SYSTEM USING NEURAL NETWORKS
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作者 Tian Sheping Ding Guoqing +1 位作者 Yan Detian Lin Liangming Department of Information Measurement and Instrumentation,Shanghai Jiaotong University,Shanghai 200030, China 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2004年第2期306-310,共5页
The pneumatic artificial muscles are widely used in the fields of medicalrobots, etc. Neural networks are applied to modeling and controlling of artificial muscle system. Asingle-joint artificial muscle test system is... The pneumatic artificial muscles are widely used in the fields of medicalrobots, etc. Neural networks are applied to modeling and controlling of artificial muscle system. Asingle-joint artificial muscle test system is designed. The recursive prediction error (RPE)algorithm which yields faster convergence than back propagation (BP) algorithm is applied to trainthe neural networks. The realization of RPE algorithm is given. The difference of modeling ofartificial muscles using neural networks with different input nodes and different hidden layer nodesis discussed. On this basis the nonlinear control scheme using neural networks for artificialmuscle system has been introduced. The experimental results show that the nonlinear control schemeyields faster response and higher control accuracy than the traditional linear control scheme. 展开更多
关键词 Artificial muscle Neural networks Recursive prediction error algorithm Nonlinear modeling and controlling
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Novel real-time safety algorithm for predicting multi-targets in the farmland road
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作者 Xiaoming Liang Fu’en Chen +4 位作者 Longhan Chen Deyue Li Bin Guo Yubo Liang Yubin Lan 《International Journal of Agricultural and Biological Engineering》 SCIE 2023年第5期198-203,共6页
The more information obtained about the driving environment,the more ensures driving safety.Due to the complex driving environment of farmland roads,targets beside the road sometimes have an important impact on drivin... The more information obtained about the driving environment,the more ensures driving safety.Due to the complex driving environment of farmland roads,targets beside the road sometimes have an important impact on driving safety.To achieve this goal,a novel real-time detection and prediction algorithm of targets was proposed.The whole image was divided into four parts by RCM:driving region,crossroad region,roadside region,and the other region.In addition,a safety policy for every part was enforced by the algorithm,which was based mainly on the combination of the YOLACT and GPM.On this basis,a self-collected data set of 5000 test samples is used for testing.The detection accuracy of the algorithm in the data set could reach up to 90%,and the processing speed to 30.4 fps.In addition,experiments were carried out on actual farmland roads,and the results showed that the proposed algorithm was able to detect,track,and predict targets on the farmland road,and alarm to driver in time before the targets rush into the road.This study provides an important reference for the safe driving of agricultural vehicles. 展开更多
关键词 REAL-TIME SAFETY algorithm for predicting MULTI-TARGET farmland road computer vision
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Alleviating limit cycling in training GANs with an optimization technique 被引量:1
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作者 Keke Li Liping Tang Xinmin Yang 《Science China Mathematics》 SCIE CSCD 2024年第6期1287-1316,共30页
In this paper,we undertake further investigation to alleviate the issue of limit cycling behavior in training generative adversarial networks(GANs)through the proposed predictive centripetal acceleration algorithm(PCA... In this paper,we undertake further investigation to alleviate the issue of limit cycling behavior in training generative adversarial networks(GANs)through the proposed predictive centripetal acceleration algorithm(PCAA).Specifically,we first derive the upper and lower complexity bounds of PCAA for a general bilinear game,with the last-iterate convergence rate notably improving upon previous results.Then,we combine PCAA with the adaptive moment estimation algorithm(Adam)to propose PCAA-Adam,for practical training of GANs to enhance their generalization capability.Finally,we validate the effectiveness of the proposed algorithm through experiments conducted on bilinear games,multivariate Gaussian distributions,and the CelebA dataset,respectively. 展开更多
关键词 GANs general bilinear game predictive centripetal acceleration algorithm lower and upper complexity bounds PCAA-Adam
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A Novel Vertical Handoff Algorithm Based on Fuzzy Logic in Aid of Grey Prediction Theory in Wireless Heterogeneous Networks 被引量:2
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作者 刘侠 蒋铃鸽 《Journal of Shanghai Jiaotong university(Science)》 EI 2012年第1期25-30,共6页
To coordinate the various access technologies in the 4G communication system,intelligent vertical handoff algorithms are required.This paper mainly deals with a novel vertical handoff decision algorithm based on fuzzy... To coordinate the various access technologies in the 4G communication system,intelligent vertical handoff algorithms are required.This paper mainly deals with a novel vertical handoff decision algorithm based on fuzzy logic with the aid of grey theory and dynamic weights adaptation.The grey prediction theory(GPT) takes 4 sampled received signal strengths as input parameters,and calculates the predicted received signal strength in order to reduce the call dropping probability.The fuzzy logic theory based quantitative decision algorithm takes 3 quality of service(QoS)metric,received signal strength(RSS),available bandwidth(BW),and monetary cost (MC)of candidate networks as input parameters.The weight of each QoS metrics is adjusted along with the networks changing to trace the network condition.The final optimized vertical handoff decision is made by comparing the quantitative decision values of the candidate networks.Simulation results demonstrate that the proposed algorithm provides high performance in heterogeneous as well as homogeneous network environments. 展开更多
关键词 fuzzy logic theory grey prediction algorithm quantitative decision vertical handoff
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An improved algorithm for noise-robust sparse linear prediction of speech 被引量:1
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作者 ZHOU Bin ZOU Xia ZHANG Xiongwei 《Chinese Journal of Acoustics》 CSCD 2015年第1期84-95,共12页
The performance of linear prediction analysis of speech deteriorates rapidly under noisy environments. To tackle this issue, an improved noise-robust sparse linear prediction algorithm is proposed. First, the linear p... The performance of linear prediction analysis of speech deteriorates rapidly under noisy environments. To tackle this issue, an improved noise-robust sparse linear prediction algorithm is proposed. First, the linear prediction residual of speech is modeled as Student-t distribution, and the additive noise is incorporated explicitly to increase the robustness, thus a probabilistic model for sparse linear prediction of speech is built, Furthermore, variational Bayesian inference is utilized to approximate the intractable posterior distributions of the model parameters, and then the optimal linear prediction parameters are estimated robustly. The experimental results demonstrate the advantage of the developed algorithm in terms of several different metrics compared with the traditional algorithm and the l1 norm minimization based sparse linear prediction algorithm proposed in recent years. Finally it draws to a conclusion that the proposed algorithm is more robust to noise and is able to increase the speech quality in applications. 展开更多
关键词 An improved algorithm for noise-robust sparse linear prediction of speech PESQ LP
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Instance-Specific Algorithm Selection via Multi-Output Learning 被引量:1
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作者 Kai Chen Yong Dou +1 位作者 Qi Lv Zhengfa Liang 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2017年第2期210-217,共8页
Instance-specific algorithm selection technologies have been successfully used in many research fields,such as constraint satisfaction and planning. Researchers have been increasingly trying to model the potential rel... Instance-specific algorithm selection technologies have been successfully used in many research fields,such as constraint satisfaction and planning. Researchers have been increasingly trying to model the potential relations between different candidate algorithms for the algorithm selection. In this study, we propose an instancespecific algorithm selection method based on multi-output learning, which can manage these relations more directly.Three kinds of multi-output learning methods are used to predict the performances of the candidate algorithms:(1)multi-output regressor stacking;(2) multi-output extremely randomized trees; and(3) hybrid single-output and multioutput trees. The experimental results obtained using 11 SAT datasets and 5 Max SAT datasets indicate that our proposed methods can obtain a better performance over the state-of-the-art algorithm selection methods. 展开更多
关键词 algorithm selection multi-output learning extremely randomized trees performance prediction constraint satisfaction
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MATTER-ELEMENT MODELING OF PARALLEL STRUCTURE AND APPLICATION ABOUT EXTENSION PID CONTROL SYSTEM 被引量:3
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作者 Rongde LU Zonghai CHEN 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2006年第2期227-235,共9页
This article describes in detail a new method via the extension predictable algorithm of the matter-element model of parallel structure tuning the parameters of the extension PID controller. In comparison with fuzzy a... This article describes in detail a new method via the extension predictable algorithm of the matter-element model of parallel structure tuning the parameters of the extension PID controller. In comparison with fuzzy and extension PID controllers, the proposed extension PID predictable controller shows higher control gains when system states are away from equilibrium, and retains a lower profile of control signals at the same time. Consequently, better control performance is achieved. Through the proposed tuning formula, the weighting factors of an extension-logic predictable controller can be systematically selected according to the control plant. An experimental example through industrial field data and site engineers' experience demonstrates the superior performance of the proposed controller over the fuzzy controller. 展开更多
关键词 Extension control system matter modeling parallel structure PID predictable algorithm.
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Ensemble Prediction of Monsoon Index with a Genetic Neural Network Model
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作者 姚才 金龙 赵华生 《Acta meteorologica Sinica》 SCIE 2009年第6期701-712,共12页
After the consideration of the nonlinear nature changes of monsoon index,and the subjective determination of network structure in traditional artificial neural network prediction modeling,monthly and seasonal monsoon ... After the consideration of the nonlinear nature changes of monsoon index,and the subjective determination of network structure in traditional artificial neural network prediction modeling,monthly and seasonal monsoon intensity index prediction is studied in this paper by using nonlinear genetic neural network ensemble prediction(GNNEP)modeling.It differs from traditional prediction modeling in the following aspects: (1)Input factors of the GNNEP model of monsoon index were selected from a large quantity of preceding period high correlation factors,such as monthly sea temperature fields,monthly 500-hPa air temperature fields,monthly 200-hPa geopotential height fields,etc.,and they were also highly information-condensed and system dimensionality-reduced by using the empirical orthogonal function(EOF)method,which effectively condensed the useful information of predictors and therefore controlled the size of network structure of the GNNEP model.(2)In the input design of the GNNEP model,a mean generating function(MGF)series of predictand(monsoon index)was added as an input factor;the contrast analysis of results of predic- tion experiments by a physical variable predictor-predictand MGF GNNEP model and a physical variable predictor GNNEP model shows that the incorporation of the periodical variation of predictand(monsoon index)is very effective in improving the prediction of monsoon index.(3)Different from the traditional neural network modeling,the GNNEP modeling is able to objectively determine the network structure of the GNNNEP model,and the model constructed has a better generalization capability.In the case of identical predictors,prediction modeling samples,and independent prediction samples,the prediction accuracy of our GNNEP model combined with the system dimensionality reduction technique of predictors is clearly higher than that of the traditional stepwise regression model using the traditional treatment technique of predictors,suggesting that the GNNEP model opens up a vast range of possibilities for operational weather prediction. 展开更多
关键词 monsoon index ensemble prediction genetic algorithm neural network mean generating function
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