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Fast source mask co-optimization method for high-NA EUV lithography
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作者 Ziqi Li Lisong Dong +1 位作者 Xu Ma Yayi Wei 《Opto-Electronic Advances》 SCIE EI CAS CSCD 2024年第4期44-54,共11页
Extreme ultraviolet(EUV)lithography with high numerical aperture(NA)is a future technology to manufacture the integrated circuit in sub-nanometer dimension.Meanwhile,source mask co-optimization(SMO)is an extensively u... Extreme ultraviolet(EUV)lithography with high numerical aperture(NA)is a future technology to manufacture the integrated circuit in sub-nanometer dimension.Meanwhile,source mask co-optimization(SMO)is an extensively used approach for advanced lithography process beyond 28 nm technology node.This work proposes a novel SMO method to improve the image fidelity of high-NA EUV lithography system.A fast high-NA EUV lithography imaging model is established first,which includes the effects of mask three-dimensional structure and anamorphic magnification.Then,this paper develops an efficient SMO method that combines the gradient-based mask optimization algorithm and the compressivesensing-based source optimization algorithm.A mask rule check(MRC)process is further proposed to simplify the optimized mask pattern.Results illustrate that the proposed SMO method can significantly reduce the lithography patterning error,and maintain high computational efficiency. 展开更多
关键词 computational lithography high-NA EUV lithography source-mask co-optimization lithography imaging model
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Multivariate analysis of oral mucosal ulcers during orthodontic treatment 被引量:1
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作者 Jing Chang Xue Li 《World Journal of Clinical Cases》 SCIE 2024年第26期5868-5876,共9页
BACKGROUND Orthodontic treatment can easily cause local soft tissue reactions in the oral cavity of patients under mechanical stress,leading to oral mucosal ulcers and affecting their quality of life.At present,only l... BACKGROUND Orthodontic treatment can easily cause local soft tissue reactions in the oral cavity of patients under mechanical stress,leading to oral mucosal ulcers and affecting their quality of life.At present,only limited literature has explored the factors leading to oral ulcers in orthodontic treatment,and these research results are still controversial.AIM To investigate the current status and related factors of oral mucosal ulcers during orthodontic treatment,aiming to provide a valuable reference for preventing this disease in clinical practice.METHODS A total of 587 patients who underwent orthodontic treatment at the Peking University School of Stomatology and Hospital of Stomatology between 2020 and 2022 were selected and allocated to an observation or control group according to the incidence of oral mucosal ulcers during orthodontic therapy.A questionnaire survey was constructed to collect patient data,including basic information,lifestyle and eating habits,treatment details,mental factors,and trace element levels,and a comparative analysis of this data was performed between the two groups.RESULTS A logistic regression model with oral ulcers as the dependent variable was established.The regression results showed that age(≥60 years:odds ratio[OR]:6.820;95%confidence interval[CI]:2.226–20.893),smoking history(smoking:OR:4.434;95%CI:2.527–7.782),toothbrush hardness(hard:OR:2.804;95%CI:1.746–4.505),dietary temperature(hot diet:OR:1.399;95%CI:1.220–1.722),treatment course(>1 year:OR:3.830;95%CI:2.203–6.659),and tooth brushing frequency(>1 time per day:OR:0.228;95%CI:0.138–0.377)were independent factors for oral mucosal ulcers(P<0.05).Furthermore,Zn level(OR:0.945;95%CI:0.927–0.964)was a protective factor against oral ulcers,while the SAS(OR:1.284;95%CI:1.197–1.378)and SDS(OR:1.322;95%CI:1.231–1.419)scores were risk factors.CONCLUSION Age≥60 years,smoking history,hard toothbrush,hot diet,treatment course for>1 year,tooth brushing frequency of≤1 time per day,and mental anxiety are independent risk factors for oral mucosal ulcers.Therefore,these factors should receive clinical attention and be incorporated into the development and optimization of preventive strategies for reducing oral ulcer incidence. 展开更多
关键词 Orthodontic treatment Oral ulcers multivariATE Logistic regression Prevent disease
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Multivariate Analysis of Female Stress Urinary Incontinence and Establishment of a Prediction Model
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作者 Lei Li Lin Luo +2 位作者 Junnai Wang Ying Hong Jianfang Geng 《Biomedical and Environmental Sciences》 SCIE CAS CSCD 2024年第8期931-935,共5页
Stress urinary incontinence(SUI)is a symptom of uncontrolled urine outflow that affects millions of women worldwide[1].SUI is a significant healthcare issue that affects the quality of life of women across numerous do... Stress urinary incontinence(SUI)is a symptom of uncontrolled urine outflow that affects millions of women worldwide[1].SUI is a significant healthcare issue that affects the quality of life of women across numerous domains,including social activities,physical health,mental well-being,employment,and sexual life. 展开更多
关键词 URINE URINARY multivariATE
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Multivariate Time Series Anomaly Detection Based on Spatial-Temporal Network and Transformer in Industrial Internet of Things
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作者 Mengmeng Zhao Haipeng Peng +1 位作者 Lixiang Li Yeqing Ren 《Computers, Materials & Continua》 SCIE EI 2024年第8期2815-2837,共23页
In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.A... In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods. 展开更多
关键词 multivariate time series anomaly detection spatial-temporal network TRANSFORMER
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Factors affecting farmers'choice to adopt risk management strategies:The application of multivariate and multinomial probit models
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作者 Jamal Shah Majed Alharthi 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第12期4250-4262,共13页
This study investigates the factors that impact farmers'adoption of risk management strategies(RMS)in Pakistan during times of uncertainty.The study examines farmers'adoption of RMS using both multinomial prob... This study investigates the factors that impact farmers'adoption of risk management strategies(RMS)in Pakistan during times of uncertainty.The study examines farmers'adoption of RMS using both multinomial probit(MNP)and multivariate probit(MVP).Data were collected from 382 farmers sampled from four districts in KhyberPakhtunkhwa(KP)province of Pakistan via a multistage sampling technique.This study utilizes the MNP model,considering the assumption of Independence of Irrelevant Alternatives(IIA)and incorporating correlated error terms.The objective is to understand farmers'behavior in risky situations and determine if there is heterogeneity.Results are compared with the MVP model to assess robustness and gain deeper understanding of farmers'decisionmaking processes.The research findings reveal that our results are robust,and farmers behave homogeneously in various RMS scenarios.Farmers adopt RMS individually or in combination to mitigate the adverse effects of natural calamities on their livelihood.The risk-averse farmers,who perceive weather-related risks as a threat,access credits and information,and have farms close to a river are more likely to adopt RMS,irrespective of the format of the strategies available.Moreover,the predicted probabilities and correlation of the RMS and RM categories have strengthened our model estimation.These findings provide insights into the behavior of farmers in adopting RMS which are helpful for policymakers and stakeholders in developing strategies to mitigate the impacts of natural calamities on farmers. 展开更多
关键词 multinomial probit model multivariate probit model risk management strategies risk-attitude risk perception
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Advancing Autoencoder Architectures for Enhanced Anomaly Detection in Multivariate Industrial Time Series
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作者 Byeongcheon Lee Sangmin Kim +2 位作者 Muazzam Maqsood Jihoon Moon Seungmin Rho 《Computers, Materials & Continua》 SCIE EI 2024年第10期1275-1300,共26页
In the context of rapid digitization in industrial environments,how effective are advanced unsupervised learning models,particularly hybrid autoencoder models,at detecting anomalies in industrial control system(ICS)da... In the context of rapid digitization in industrial environments,how effective are advanced unsupervised learning models,particularly hybrid autoencoder models,at detecting anomalies in industrial control system(ICS)datasets?This study is crucial because it addresses the challenge of identifying rare and complex anomalous patterns in the vast amounts of time series data generated by Internet of Things(IoT)devices,which can significantly improve the reliability and safety of these systems.In this paper,we propose a hybrid autoencoder model,called ConvBiLSTMAE,which combines convolutional neural network(CNN)and bidirectional long short-term memory(BiLSTM)to more effectively train complex temporal data patterns in anomaly detection.On the hardware-in-the-loopbased extended industrial control system dataset,the ConvBiLSTM-AE model demonstrated remarkable anomaly detection performance,achieving F1 scores of 0.78 and 0.41 for the first and second datasets,respectively.The results suggest that hybrid autoencoder models are not only viable,but potentially superior alternatives for unsupervised anomaly detection in complex industrial systems,offering a promising approach to improving their reliability and safety. 展开更多
关键词 Advanced anomaly detection autoencoder innovations unsupervised learning industrial security multivariate time series analysis
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AFSTGCN:Prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network
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作者 Yuteng Xiao Kaijian Xia +5 位作者 Hongsheng Yin Yu-Dong Zhang Zhenjiang Qian Zhaoyang Liu Yuehan Liang Xiaodan Li 《Digital Communications and Networks》 SCIE CSCD 2024年第2期292-303,共12页
The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries an... The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models. 展开更多
关键词 Adaptive adjacency matrix Digital twin Graph convolutional network multivariate time series prediction Spatial-temporal graph
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A New Method for Constructing the Inversion of Multivariable Linear Systems
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作者 张新建 童丽 《Chinese Quarterly Journal of Mathematics》 CSCD 2001年第4期18-24,共7页
A new algorithm for constructing an inverse of a multivariable linear system is presented. This algorithm makes the constructing an inverse of the higher order matrices into searching for the equivalent normal form o... A new algorithm for constructing an inverse of a multivariable linear system is presented. This algorithm makes the constructing an inverse of the higher order matrices into searching for the equivalent normal form of the lower order matrices. Consequently, the calculation is more simple efficient and programmed than previous methods. Another result of the paper is that the lower reduced inverse system is obtained, by selecting special bases of the observable space of the original systems, it reveals the effect of the observability of the original systems on the order of the inverse systems. 展开更多
关键词 multivariable linear system inverse system orthogonal decomposition
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Multivariable Fuzzy Predictive Control Based on the Modified CPN Model
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作者 郑怀林 陈维南 《Journal of Southeast University(English Edition)》 EI CAS 1998年第1期108-113,共6页
Through modifying the CPN model, a kind of multivariable fuzzy model is put forward, and the matching fuzzy multistep predictive control algorithm is deduced based on the model. The modified model works in a competiti... Through modifying the CPN model, a kind of multivariable fuzzy model is put forward, and the matching fuzzy multistep predictive control algorithm is deduced based on the model. The modified model works in a competitive output manner which results in its local representation property. While studying on line, only a few parameters need to be regulated. So the model has the merits of fast learning and on line self organizing modeling. The control algorithm is simple, adaptive and useful in multivariable and time delay systems. Applying the algorithm in a paper making system, simulation shows its good effect. 展开更多
关键词 modified CPN model fuzzy predictive control multivariable time delay systems
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MULTIVARIABLE MODEL REFERENCE ADAPTIVE CONTROL FOR A TURBOFAN ENGINE 被引量:6
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作者 Fan Jun Huang Jinquan +1 位作者 Sun Jianguo Feng Zhengping(Dep. Of Power Engineering, Nanjing University of Aeronauticsand Astronautics, Nanjing,China, 210026) 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 1996年第4期300-304,共5页
A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performan... A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performance of the system over the fullflight envelope. Simulation results also show the good effectiveness of reducing interactionin the multivariable system with significant coupling. The control system developed has awide frequency band to satisfy the strict engineering requirement and is practical for engineering applications. 展开更多
关键词 turbofan engines model reference adaptive control flight envelopes multivariable control
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Multivariable PI Type Generalized Predictive Control 被引量:4
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作者 Chen, Zengqiang Zhao, Tianhang Yuan, Zhuzhi 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 1998年第2期8-13,共6页
This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatl... This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatly. The effectiveness of the controller is demonstrated by the simulation result. 展开更多
关键词 Predictive control Self-tuning control multivariable control PI control
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Multivariable Decoupling Predictive Control with Input Constraints and Its Application on Chemical Process 被引量:13
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作者 苏佰丽 陈增强 袁著祉 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2006年第2期216-222,共7页
A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solvin... A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy. 展开更多
关键词 chemical process control multivariable system OPTIMIZATION predictive control input constraint
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Incremental multivariable predictive functional control and its application in a gas fractionation unit 被引量:3
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作者 施惠元 苏成利 +3 位作者 曹江涛 李平 宋英莉 李宁波 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第12期4653-4668,共16页
The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the t... The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the traditional PID control has been proven not sufficient and capable for this particular petro-chemical process.In this work,an incremental multivariable predictive functional control(IMPFC) algorithm was proposed with less online computation,great precision and fast response.An incremental transfer function matrix model was set up through the step-response data,and predictive outputs were deduced with the theory of single-value optimization.The results show that the method can optimize the incremental control variable and reject the constraint of the incremental control variable with the positional predictive functional control algorithm,and thereby making the control variable smoother.The predictive output error and future set-point were approximated by a polynomial,which can overcome the problem under the model mismatch and make the predictive outputs track the reference trajectory.Then,the design of incremental multivariable predictive functional control was studied.Simulation and application results show that the proposed control strategy is effective and feasible to improve control performance and robustness of process. 展开更多
关键词 gas fractionation unit multivariable process incremental predictive functional control
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A method for real power transfer allocation using multivariable regression analysis 被引量:6
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作者 Hussain Shareef Azah Mohamed +1 位作者 Saifunizam Abd.Khalid Mohd Wazir Mustafa 《Journal of Central South University》 SCIE EI CAS 2012年第1期179-186,共8页
A multivariable regression(MVR) approach is proposed to identify the real power transfer between generators and loads.Based on solved load flow results,it first uses modified nodal equation method(MNE) to determine re... A multivariable regression(MVR) approach is proposed to identify the real power transfer between generators and loads.Based on solved load flow results,it first uses modified nodal equation method(MNE) to determine real power contribution from each generator to loads.Then,the results of MNE method and load flow information are utilized to determine suitable regression coefficients using MVR model to estimate the power transfer.The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of the MVR output compared to that of the MNE method.The error of the estimate of MVR method ranges from 0.001 4 to 0.007 9.Furthermore,when compared to MNE method,MVR method computes generator contribution to loads within 26.40 ms whereas the MNE method takes 360 ms for the calculation of same real power transfer allocation.Therefore,MVR method is more suitable for real time power transfer allocation. 展开更多
关键词 power tracing multivariable regression power systems DEREGULATION
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Multivariable sales prediction for filling stations via GA improved BiLSTM 被引量:6
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作者 Shi-Yuan Pan Qi Liao Yong-Tu Liang 《Petroleum Science》 SCIE CAS CSCD 2022年第5期2483-2496,共14页
Accurate sales prediction in filling stations is the basis to fill in the refined oil in time and avoid the outof-stock as much as possible.Considering the defect of great“lag”in the general time series model,this p... Accurate sales prediction in filling stations is the basis to fill in the refined oil in time and avoid the outof-stock as much as possible.Considering the defect of great“lag”in the general time series model,this paper summarizes the multiple factors that influence the oil sales and develops a multivariable long short-term memory(LSTM)neural network,with the hyper-parameters being improved by the genetic algorithm(GA).To further improve the prediction accuracy,the proposed LSTM neural network is generalized to bidirectional LSTM(Bi LSTM),in which the impact of future factors on present sales can be taken into account by backward training.Finally,different LSTM structures and genetic algorithm parameters are tested to discuss their impact on prediction accuracy.Results demonstrated that genetic algorithm improved Bi LSTM model is superior to extreme gradient boosting,ARIMA,and artificial neural network,having the highest accuracy of 89%. 展开更多
关键词 Refined oil multivariable prediction BiLSTM Genetic algorithm Future influence
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Multivariable Decoupling Predictive Control Based on QFT Theory and Application in CSTR Chemical Process 被引量:4
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作者 王增会 陈增强 +1 位作者 孙青林 袁著祉 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2006年第6期765-769,共5页
A novel method of incorporating generalized predictive control (GPC) algorithms based on quantitative feedback theory (QFT) principles is proposed for solving the feedback control problem of the highly uncertain and c... A novel method of incorporating generalized predictive control (GPC) algorithms based on quantitative feedback theory (QFT) principles is proposed for solving the feedback control problem of the highly uncertain and cross-coupling plants. The quantitative feedback theory decouples the multi-input and multi-output (MIMO) plant and is also used to reduce the uncertainties of the system, stabilize the system, and achieve tracking performance of the system to a certain extent. Single-input and single-output (SISO) generalized predictive control is used to achieve performance with higher performance. In GPC, the model is identified on-line, which is based on the QFT input and the plant output signals. The simulation results show that the performance of the system is superior to the performance when only QFT is used for highly uncertain MIMO plants. 展开更多
关键词 quantitative feedback theory generalized PREDICTIVE control decouple multivariable uncertain system frequency domain design
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Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms 被引量:7
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作者 ANDRES-TOROB. GIRON-SIERRAJ.M. FERNANDEZ-BLANCOP. LOPEZ-OROZCOJ.A. BESADA-PORTASE. 《Journal of Zhejiang University Science》 CSCD 2004年第4期378-389,共12页
This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathe... This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results.The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs).Successful finding of optimal ways to drive these processes were reported.Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules. 展开更多
关键词 Multiobjective optimization Genetic algorithms Industrial control multivariable control systems Fermenta- tion processes
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PSEUDO-DIVISION ALGORITHM FOR MATRIX MULTIVARIABLE POLYNOMIAL AND ITS APPLICATION 被引量:1
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作者 阿拉坦仓 张鸿庆 钟万勰 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2000年第7期733-740,共8页
Pseudo-division algorithm for matrix multivariable polynomial are given, thereby with the view of differential algebra, the sufficient and necessary conditions for transforming a class of partial differential equation... Pseudo-division algorithm for matrix multivariable polynomial are given, thereby with the view of differential algebra, the sufficient and necessary conditions for transforming a class of partial differential equations into infinite dimensional Hamiltonianian system and its concrete form are obtained. Then by combining this method with Wu's method, a new method of constructing general solution of a class of mechanical equations is got, which several examples show very effective. 展开更多
关键词 matrix multivariable polynomial infinite dimensional Hamiltonianian system Wu's method general solution
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ANALYSIS OF BENDING, VIBRATION AND STABILITY FOR THIN PLATE ON ELASTIC FOUNDATION BY THE MULTIVARIABLE SPLINE ELEMENT METHOD 被引量:1
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作者 沈鹏程 何沛祥 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 1997年第8期779-787,共9页
In this paper, the bicubic splines in product form are used to construct the multi-field functions for bending moments, twisting moment and transverse displacement of the plate on elastic foundation. The multivariable... In this paper, the bicubic splines in product form are used to construct the multi-field functions for bending moments, twisting moment and transverse displacement of the plate on elastic foundation. The multivariable spline element equations are derived, based on the mixed variational principle. The analysis and calculations of bending, vibration and stability of the plates on elastic foundation are presented in the paper. Because the field functions of plate on elastic foundation are assumed independently, the precision of the field variables of bending moments and displacement is high. 展开更多
关键词 multivariable spline element method bicubic B spline plate on elastic foundation
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Medium-Term Electric Load Forecasting Using Multivariable Linear and Non-Linear Regression 被引量:2
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作者 Nazih Abu-Shikhah Fawwaz Elkarmi Osama M. Aloquili 《Smart Grid and Renewable Energy》 2011年第2期126-135,共10页
Medium-term forecasting is an important category of electric load forecasting that covers a time span of up to one year ahead. It suits outage and maintenance planning, as well as load switching operation. We propose ... Medium-term forecasting is an important category of electric load forecasting that covers a time span of up to one year ahead. It suits outage and maintenance planning, as well as load switching operation. We propose a new methodol-ogy that uses hourly daily loads to predict the next year hourly loads, and hence predict the peak loads expected to be reached in the next coming year. The technique is based on implementing multivariable regression on previous year's hourly loads. Three regression models are investigated in this research: the linear, the polynomial, and the exponential power. The proposed models are applied to real loads of the Jordanian power system. Results obtained using the pro-posed methods showed that their performance is close and they outperform results obtained using the widely used ex-ponential regression technique. Moreover, peak load prediction has about 90% accuracy using the proposed method-ology. The methods are generic and simple and can be implemented to hourly loads of any power system. No extra in-formation other than the hourly loads is required. 展开更多
关键词 Medium-Term LOAD Forecasting Electrical PEAK LOAD multivariable Regression And TIME SERIES
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