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Forecast model of agricultural circular economy development trend based on gp algorithm

TURKISH JOURNAL OF AGRICULTURE AND FORESTRY 2024年第1期48卷 43-56页

作者： Yin, Yue Ning, Weidong Northeast Agr Univ Sch Publ Adm & Law Harbin Peoples R China Mudanjiang Med Univ Sch Hlth Management Mudanjiang Peoples R China

To thoroughly and objectively analyze the developmental status of the agricultural circular economy and accurately forecast its future trends, we delved into a predictive model utilizing the gp algorithm. Building upon this foundation, we formulated an evaluation system for the agricultural circular economy's progression, taking into account economic and social development, resource reduction and investment, resource recycling, environmental impact, and population dynamics. To streamline the evaluation process, we employed the kernel principal component analysis method to condense the indicator system's dimensions for agricultural circular economy development. The reduced dimensionality, representing the agricultural circular economy development index, served as input for the gp algorithm. Enhancements were made to the gp algorithm through a fixed structure, multipopulation, and coefficient climbing method. Ultimately, we applied the refined gp algorithm to anticipate the developmental trajectory of the agricultural circular economy. The findings suggest that the model presented in this article successfully forecasts the agricultural circular economy, holding significant implications for advancing its further development.

关键词： gp algorithm agricultural cycle economic development trend trend prediction model index system kernel principal component analysis

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Research on Electricity Theft Identification Method Based on Multi-Component Feature Fusion

Research on Electricity Theft Identification Method Based on...

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2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025

作者： Wu, Yuli Zheng, Chenyang School of Electrical and Control Engineering Liaoning Project Technology University Huludao125000 China

ISBN: (纸本)9798331506797

The huge amount of electricity consumption data in the smart grid makes data-driven electricity theft detection possible, but extracting features from electricity consumption time series that can help electricity theft detection is a challenging problem. To address this problem, a power theft user identification method based on STL decomposition and feature fusion is proposed. Firstly, the original sequence is decomposed into trend, seasonal and residual components using a robust STL decomposition method;then, according to the characteristics of each component, the features of the trend and seasonal components are extracted using an LSTM neural network with an attentional mechanism (Att-LSTM) and a one-dimensional convolutional neural network (1D-CNN), respectively;for the residual component, it is treated by a dynamics system analysis method is processed and the fractal dimension is calculated as its feature by gp algorithm;finally, the three component features are fused using a fully connected layer with attention mechanism for electricity theft user identification and compared with other methods. The results show that the feature extraction method used in this paper can effectively extract the features of electricity theft, and the method can accurately identify the electricity theft users. © 2025 IEEE.

关键词： dynamical system analysis fractal dimension gp algorithm neural networks STL decomposition

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Characterizing isolated attosecond pulses from hollow-core waveguides using multi-cycle driving pulses

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OPTICS EXPRESS 2009年第6期17卷 4611-4633页

作者： Thomann, I. Bahabad, A. Liu, X. Trebino, R. Murnane, M. M. Kapteyn, H. C. Univ Colorado JILA Boulder CO 80309 USA NIST Boulder CO 80309 USA Georgia Inst Technol Sch Phys Atlanta GA 30332 USA

The generation of attosecond-duration light pulses using the high-order harmonic generation process is a rapidly evolving area of research. In this work, we combine experimental measurements with careful numerical analysis, to demonstrate that even relatively long-duration, 15 fs, carrier-envelope-phase (CEP) unstabilized near-infrared (NIR) pulses can generate isolated attosecond extreme-ultraviolet (EUV) pulses by the dynamically-changing phase matching conditions in a hollow-core waveguide geometry. The measurements are made using the laser-assisted photoelectric effect to cross-correlate the EUV pulse with the NIR pulse. A FROG CRAB analysis of the resulting traces (photoelectron signal versus photoelectron energy and EUV-NIR delay) is performed using a generalized projections (gp) algorithm, adapted for a wide-angle photoelectron detection geometry and non-CEP stabilized driving laser pulses. In addition, we performed direct FROG CRAB simulations under the same conditions. Such direct simulations allow more freedom to explore the effect of specific pulse parameters on FROG CRAB traces than is possible using the automated gp retrieval algorithm. Our analysis shows that an isolated pulse with duration of approximate to 200 attoseconds can result from CEP unstabilized, high intensity approximate to 15 fs multi-cycle driving pulses coupled into a hollow-core waveguide filled with low-pressure Argon gas. These are significantly longer driving pulses than used in other experimental implementations of isolated attosecond pulses. (C) 2009 Optical Society of America

关键词： .harmonic generation characterizing direct simulations attosecond pulses pulses using driving laser multi-cycle hollow-core waveguide EUV pulse gp algorithm FROG CRAB traces

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Evolutionary Modeling for Streamflow Forecasting with Minimal Datasets: A Case Study in the West Malian River, China

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ENVIRONMENTAL ENGINEERING SCIENCE 2010年第5期27卷 377-385页

作者： Ni, Qingwei Wang, Li Ye, Renzhen Yang, Fenglin Sivakumar, Muttucumaru Shenyang Univ Chem Technol Coll Environm & Biol Engn Shenyang 110142 Peoples R China Dalian Univ Technol Sch Environm & Biol Sci & Technol Dalian Peoples R China Agr Univ Huazhong Dept Math Wuhan Peoples R China Univ Wollongong Sch Civil Min & Environm Engn Wollongong NSW Australia

A large dataset is generally needed when modeling hydrological processes. However, for developing countries such as China, datasets are often unavailable in remote areas. An attempt to apply a novel genetic programming (gp) technique was made to model the relationship between streamflow of the West Malian River and the impact of climate change in the northeastern part of China. Available annual streamflow and climatic data were used for training and testing of the gp model. Data from the years between 1982 and 2002 were used for automatic selection of the model relationship. Prediction of the model was undertaken for the period 2003-2006 and the results were compared with measured data. Predicted annual streamflow of the West Malian River agreed with measured data to an acceptable degree of accuracy even with a small amount of dataset. For comparison, a multilayer perceptron method with back propagation algorithm, a gray theory model, and a multiple linear regression model were selected to conduct the prediction with the same dataset. Results showed that the performance of gp method was generally better than other statistical methods such as multilayer perceptron, gray theory model, and multiple linear regression model. Further, the results also showed that the gp method is a useful tool for water resource management, especially in developing countries, to evaluate the potential impacts of climate change on the streamflow when large datasets are unavailable.

关键词： annual streamflow evaporation gp algorithm precipitation statistical methods West Malian River

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Logical genetic programming (Lgp) application to water resources management

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2020年第1期192卷 34-34页

作者： Ashofteh, Parisa-Sadat Bozorg-Haddad, Omid Loaiciga, Hugo A. Univ Qom Dept Civil Engn Qom Iran Univ Tehran Dept Irrigat & Reclamat Fac Agr Engn & Technol Coll Agr & Nat Resources Tehran Iran Univ Calif Santa Barbara Dept Geog Santa Barbara CA 93106 USA

Genetic programming (gp) is a variant of evolutionary algorithms (EA). EAs are general-purpose search algorithms. Yet, gp does not solve multi-conditional problems satisfactorily. This study improves the gp's predictive skill by development and integration of mathematical logical operators and functions to it. The proposed improvement is herein named logical genetic programming (Lgp) whose performance is compared with that of gp using examples from the fields of mathematics and water resources. The results of the examples show the Lgp's superior performance in both examples, with Lgp producing improvements of 74 and 42% in the objective functions of the mathematical and water resources examples, respectively, when compared with the gp's results. The objective functions minimize the mean absolute error (MAE). The comparison of the Lgp and gp results with alternative performance criteria demonstrate a better capability of the former algorithm in solving multi-conditional problems.

关键词： gp algorithm Lgp approach Standard operating procedure (SOP) rule Logical operators Logical functions Multi-conditional mathematical problem

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Classification of surface EMG signal with fractal dimension

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2005年第8期6卷 844-848页

作者：胡晓王志中任小梅 Department of Biomedical Engineering Shanghai Jiaotong UniversityShanghai 200030 China

Surface EMG (electromyography) signal is a complex nonlinear signal with low signal to noise ratio (SNR). This paper is aimed at identifying different patterns of surface EMG signals according to fractal dimension. Two patterns of surface EMG signals are respectively acquired from the right forearm flexor of 30 healthy volunteers during right forearm supination (FS) or forearm pronation (FP). After the high frequency noise is filtered from surface EMG signal by a low-pass filter, fractal di-mension is calculated from the filtered surface EMG signal. The results showed that the fractal dimensions of filtered FS surface EMG signals and those of filtered FP surface EMG signals distribute in two different regions, so the fractal dimensions can rep-resent different patterns of surface EMG signals.

关键词： Surface EMG signal Fractal dimension Correlation dimension Self-similarity gp algorithm

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A stochastic hybrid optimization algorithm to calibration conceptual hydrologic model parameters

A stochastic hybrid optimization algorithm to calibration co...

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2nd International Conference on Information and Computing Science

作者： Hao, Zhen-chun Du, Fu-hui Hohai Univ State Key Lab Water Resources & Hydropower Engn S Nanjing Peoples R China

ISBN: (纸本)9780769536347

Combining the approximate gradient-based steepest descent algorithm and the pattern search algorithm the author present gp algorithm, a new local optimization algorithm for conceptual hydrologic model parameters. with Nash facticity coefficient as the target function the random search techniques was used for search parameter space, then optimize the selected parameter set using gp algorithm. The global optimization parameter is achieved by filtering parameter space strategy. The method above-mentioned comprise the derivative information and stochastic properties, make the optimization set escape the local maximum to the global set. The practical efficiency was verified by using a case in Yang Lou unite drainage basin. It was shown that parameters of hydrologic model can successfully be automatically calibrated.

关键词： gp algorithm stochastic optimization parameters calibration Xinanjiang model

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A Improved Way for Fault Diagnose Based on EEMD and SVM 29

A Improved Way for Fault Diagnose Based on EEMD and SVM

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第29届中国控制与决策会议

作者： Ping Yang MingLiang Liu QuanWei Peng YaoWen Xing Bin Li HLJ Province Key Lab of Senior-Education for Electronic Engineering(Heilongjiang University)

ISBN: (纸本)9781509046584

The change of the vibration signal can reflect the mechanical state of the HV circuit *** efficient method of feature extraction of the vibration signal usually pays a key role in the validity of the fault diagnosis and also lays the foundation for the fault classification in the subsequent *** paper presented a feature extraction method which is based on average empirical mode decomposition(EEMD) and gp *** EEMD algorithm is used to decompose the non-stationary signal into several the conqueror functions(IMFs).However,the first four orders usually have great influence on the classification of signal,so we select the first four orders to calculate the correlation ***,the SVM(Support Vector Machine) is used to classify different types of fault signals after decomposing(EEMD) and calculating correlation *** test indicates that the represented method have a high recognition *** a certain extent,the method is likely to provide a new method for fault diagnosis.

关键词： EEMD SVM gp algorithm HV circuit breaker and DAG-SVMS

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A Genetic Programming Approach for Fraud Detection in Electronic Transactions

A Genetic Programming Approach for Fraud Detection in Electr...

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IEEE Symposium on Computational Intelligence in Cyber Security

作者： Assis, Carlos A. S. Pereira, Adriano C. M. Pereira, Marconi A. Carrano, Eduardo G. Ctr Fed Educ Tecnol Minas Gerais PPGMMC Belo Horizonte MG Brazil Univ Fed Minas Gerais DCC Belo Horizonte MG Brazil Univ Fed Sao Joao Del Rei DETCH Ouro Branco MG Brazil Univ Fed Minas Gerais DEE Belo Horizonte MG Brazil

ISBN: (纸本)9781479945214

The volume of online transactions has increased considerably in the recent years. Consequently, the number of fraud cases has also increased, causing billion dollar losses each year worldwide. Therefore, it is mandatory to employ mechanisms that are able to assist in fraud detection. In this work, it is proposed the use of Genetic Programming (gp) to identify frauds (charge back) in electronic transactions, more specifically in online credit card operations. A case study, using a real dataset from one of the largest Latin America electronic payment systems, has been conducted in order to evaluate the proposed algorithm. The presented algorithm achieves good performance in fraud detection, obtaining gains up to 17% with regard to the actual company baseline. Moreover, several classification problems, with considerably different datasets and domains, have been used to evaluate the performance of the algorithm. The effectiveness of the algorithm has been compared with other methods, widely employed for classification. The results show that the proposed algorithm achieved good classification effectiveness in all tested instances.

关键词： credit transactions electronic commerce fraud genetic algorithms pattern classification transaction processing gp algorithm Latin America electronic payment systems algorithm performance evaluation charge back classification problems company baseline electronic transactions fraud detection fraud identification genetic programming approach online credit card operations online transactions Accuracy Companies Credit cards Genetic programming Sociology Statistics Training Genetic algorithm (GA) Fraud vandalism online transactions Credit cards credit transactions forgery Sociology electronic commerce Pattern recognition Companies Functional training

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The study on the parameters used in calculating correlative dimension

The study on the parameters used in calculating correlative ...

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4th IASTED International Conference on Circuits, Signals, and Systems

作者： Dang, Jianwu Jiangxi Univ Finance & Econ Sch Elect Sci Nanchang 330013 Jiangxi Peoples R China

ISBN: (纸本)9780889866058

In the numerical value analysis of fractal dimension based on one-dimension data series, the analyzing results achieved by different parameters are difference. This should affect the quantitative analysis of fractal system characteristics and the reliability of results achieved. In this paper, the parameters used in calculating correlative dimension with G.P. algorithm are studied both in theory and in practice. The criterion of the choice of the dimensions of the phase space reconstructed is discussed. The volume of one-dimension data series is analyzed. The range of the scalar quantity r and its data sequence is proposed. Some conclusions are achieved which should be useful for the application of fractal theory in radar signal processing, seismic data processing, underwater acoustic signal analyzing, target recognition and other fields.

关键词： fractal theory gp algorithm reconstruction phase space correlative dimension and time-series

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