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Short-term price forecasting of Nordic power market by combination Levenberg-Marquardt and cuckoo search algorithms

IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第13期9卷 1553-1563页

作者： Kim, Mun Kyeom Chung Ang Univ Dept Energy Syst Engn Seoul 604714 South Korea

This study proposes a new forecasting method for short-term spot prices in the Nordic power market. It proposes a cuckoo search Levenberg-Marquardt (CSLM)-trained, CSLM feed-forward neural network (CSLM-FFNN) for the solving process that combines the improved Levenberg Marquardt and cuckoo search algorithms. The proposed model considers actual power generation and system load as input sets to facilitate the efficient use of both transmission and power generation resources by direct market participants. During the training, the proposed CSLM-FFNN model generalises the relationship between the area prices and the system price for the same period. The model can be updated to track online the variation trend of the electricity price and to maintain accuracy because of the rapid training speed in CSLM learning algorithm. The developed model is tested with publicly available data acquired from the Nord Pool, and the model's performance is compared with state-of-the-art artificial neural networks and time-series models. Besides, the proposed approach is applied to forecast market-clearing price in the Spanish electricity market, to further assess the validity of the approach. The results show that the proposed CSLM-FFNN exhibits superior performance than other methods in terms of forecasting accuracy and training efficiency.

关键词： power markets power generation economics pricing economic forecasting feedforward neural nets learning (artificial intelligence) time series power engineering computing search problems short-term price forecasting Nordic power market Levenberg-Marquardt algorithms cuckoo search algorithms spot prices feedforward neural network FFNN system load transmission resources power generation resources direct market participants electricity price CSLM learning algorithm artificial neural networks time-series models ANN forecasting accuracy training efficiency

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Effective Constrained Handling by Hybridized cuckoo search Algorithm with Box Complex Method

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IFAC-PapersOnLine 2017年第2期50卷 209-214页

作者： Zade, Anita Patel, Narendra Padhiyar, Nitin Indian Institute of Technology Gandhinagar GandhinagarGujarat382355 India Vishwakarma Government Engineering College AhmedabadGujarat382424 India

cuckoo search algorithm (CSA) is an evolutionary optimization algorithm, which requires an additional constraint handling mechanism. While CSA has been successfully applied for exploring the search space, it lacks good convergence property near the optimum point. On the other hand Box Complex method (BCM) has good local convergence property. This paper presents a hybrid cuckoo search algorithm (CSA) with effective constraint handling mechanism by Box Complex method (BCM). Each infeasible member is processed using BCM by projecting it through the centroid of a fixed number of feasible members. This hybridization approach provides good convergence rate along with an effective constraint handling technique. To demonstrate the efficacy of the proposed algorithm, a comparative study with the other popular algorithms has been presented using eleven test problems and an optimal grade transition problem. © 2017

关键词： Evolutionary algorithms Constrained optimization Learning algorithms Complex methods Constraint handling Convergence properties cuckoo search algorithms Effective constraints Evolutionary optimization algorithm Optimal grade transition PMMA

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cuckoo search Optimization for Short Term Wind Energy Forecasting

Cuckoo Search Optimization for Short Term Wind Energy Foreca...

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IEEE Congress on Evolutionary Computation (CEC) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Barbosa, Carlos Eduardo M. Vasconcelos, Germano C. Univ Fed Pernambuco Ctr Informat Recife PE Brazil

ISBN: (纸本)9781509006229

Energy produced by wind farms is already responsible for a relevant portion of world's renewable energy and is increasingly becoming more important in modern society. As energy produced by wind farms is highly dependent on wind speed, it is not generated with regular output values requiring good forecasting systems to ensure good electricity supply. cuckoo search is a method recently introduced as a promising optimization algorithm for parameter estimation in some aplications and in this work it is investigated in wind energy forecasting. cuckoo search is compared to other popular nature inspired techniques to predict the output values of wind parks in Texas and Montana, both in the USA. Results showed, with statistical significance, cuckoo search (CS) and Self Adaptive cuckoo search (SACS) not only presented higher prediction performance when compared to PSO, ACO and a hybrid of both but also converged significantly faster than the other algorithms.

关键词： wind farms forecasting cuckoo search algorithms

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Ensuring Information Security in Electronic Health Record System Using Cryptography and cuckoo search Algorithm

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Journal of Information Hiding and Privacy Protection 2023年第1期5卷 1-18页

作者： Arkan Kh Shakr Sabonchi Zainab Hashim Obaid Department of Mathematics Open Educational CollegeKirkuk BranchKirkuk36001Iraq Mutafaweqat High School for Girls Kirkuk BranchKirkuk36001Iraq

In the contemporary era,the abundant availability of health information through internet and mobile technology raises *** and maintaining the confidentiality of patients’medical data becomes paramount when sharing such information with authorized healthcare *** electronic patient records and the internet have facilitated the exchange of medical information among healthcare providers,concerns persist regarding the security of the *** security of Electronic Health Record Systems(EHRS)can be improved by employing the cuckoo search Algorithm(CS),the SHA-256 algorithm,and the Elliptic Curve Cryptography(ECC),as proposed in this *** suggested approach involves usingCS to generate the ECCprivate key,thereby enhancing the security of data storage in *** study evaluates the proposed design by comparing encoding and decoding times with alternative techniques like *** research findings indicate that the proposed design achieves faster encoding and decoding times,completing 125 and 175 iterations,***,the proposed design surpasses other encoding techniques by exhibiting encoding and decoding times that are more than 15.17%*** results imply that the proposed design can significantly enhance the security and performance of *** the utilization of CS,SHA-256,and ECC,this study presents promising methods for addressing the security challenges associated with EHRs.

关键词： Information security electronic health record system cryptography cuckoo search algorithms

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Optimization of interval type-2 fuzzy systems for image edge detection

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APPLIED SOFT COMPUTING 2016年第0期47卷 631-643页

作者： Gonzalez, Claudia I. Melin, Patricia Castro, Juan R. Castillo, Oscar Mendoza, Olivia Univ Autonoma Baja California Tijuana Mexico Tijuana Inst Technol Tijuana Mexico

This paper presents the optimization of a fuzzy edge detector based on the traditional Sobel technique combined with interval type-2 fuzzy logic. The goal of using interval type-2 fuzzy logic in edge detection methods is to provide them with the ability to handle uncertainty in processing real world images. However, the optimal design of fuzzy systems is a difficult task and for this reason the use of meta heuristic optimization techniques is also considered in this paper. For the optimization of the fuzzy inference systems, the cuckoo search (CS) and Genetic algorithms (GAs) are applied. Simulation results show that using an optimal interval type-2 fuzzy system in conjunction with the Sobel technique provides a powerful edge detection method that outperforms its type-1 counterparts and the pure original Sobel technique. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Interval type-2 fuzzy logic Edge detection Image processing cuckoo search algorithms

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cuckoo search Algorithm Based On Local Optimization In The PID Parameter Optimization

Cuckoo Search Algorithm Based On Local Optimization In The P...

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2016 2nd Workshop on Advanced Research and Technology in Industry Applications(WARTIA 2016)

作者： Lei Luo Lixia Lv School of Control and Computer Engineering North China Electric Power University

In order to solve the problem that the cuckoo search algorithm is easy to fall into local optimal value and cannot find global optimal value,propose improved cuckoo search algorithm based on local search optimization *** extreme dynamic optimization algorithm local search operator is introduced into the latter part of the search cuckoo,make cuckoo search algorithm find that the global optimum value terms have better ***,the cuckoo algorithm applied to PID parameters optimization,and achieved satisfactory parameters.

关键词： cuckoo search algorithms local optimization PID parameter

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