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An optimal robust digital image watermarking based on SVD using differential evolution algorithm

OPTICS COMMUNICATIONS 2009年第5期282卷 769-777页

作者： Aslantas, Veysel Erciyes Univ Fac Engn Dept Comp Engn TR-38039 Kayseri Turkey

The main objective in developing a robust image watermarking technique is to obtain the highest possible robustness without losing the transparency. To achieve this objective, this paper presents a new optimal robust image watermarking technique based on singular value decomposition (SVD) using differential evolution algorithm (DE). The singular values (SV) of the host image are modified by multiple scaling factors to embed a watermark image. The modifications are optimised using DE to achieve maximum robustness and transparency Experimental results show that the proposed approach can effectively improve the quality of the watermarked image and the robustness of the embedded watermark against various attacks. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Robust image watermarking Singular value decomposition differential evolution algorithm

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USING AN IMPROVED BEE MEMORY differential evolution algorithm FOR PARAMETER ESTIMATION TO SIMULATE BIOCHEMICAL PATHWAYS

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JOURNAL OF BIOLOGICAL SYSTEMS 2014年第1期22卷 101-121页

作者： Chong, Chuii Khim Mohamad, Mohd Saberi Deris, Safaai Shamsir, Mohd Shahir Chai, Lian En Choon, Yee Wen Univ Teknol Malaysia Fac Comp Artificial Intelligence & Bioinformat Res Grp Utm Skudai 81310 Johor Malaysia Univ Teknol Malaysia Fac Biosci & Med Engn Dept Biol Sci Utm Skudai 81310 Johor Malaysia

When analyzing a metabolic pathway in a mathematical model, it is important that the essential parameters are estimated correctly. However, this process often faces few problems like when the number of unknown parameters increase, trapping of data in the local minima, repeated exposure to bad results during the search process and occurrence of noisy data. Thus, this paper intends to present an improved bee memory differential evolution (IBMDE) algorithm to solve the mentioned problems. This is a hybrid algorithm that combines the differential evolution (DE) algorithm, the Kalman filter, artificial bee colony (ABC) algorithm, and a memory feature. The aspartate and threonine biosynthesis pathway, and cell cycle pathway are the metabolic pathways used in this paper. For three production simulation pathways, the IBMDE managed to robustly produce the estimated optimal kinetic parameter values with significantly reduced errors. Besides, it also demonstrated faster convergence time compared to the Nelder-Mead (NM), simulated annealing (SA), the genetic algorithm (GA) and DE, respectively. Most importantly, the kinetic parameters that were generated by the IBMDE have improved the production rates of desired metabolites better than other estimation algorithms. Meanwhile, the results proved that the IBMDE is a reliable estimation algorithm.

关键词： Parameter Estimation differential evolution algorithm Kalman Filter Artificial Bee Colony algorithm Memory Feature

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Parameter estimation of Wiener-Hammerstein system based on multi-population self-adaptive differential evolution algorithm

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ENGINEERING COMPUTATIONS 2023年第9/10期40卷 2248-2269页

作者： Chu, Jie Li, Junhong Jiang, Yizhe Song, Weicheng Zong, Tiancheng Nantong Univ Sch Elect Engn Nantong Peoples R China

PurposeThe Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) ***/methodology/approachThe idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, *** the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA ***/valueCompared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input-output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.

关键词： Wiener-Hammerstein Nonlinear system identification differential evolution algorithm Multi-population Self-adaptive

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The energy demand estimation for Turkey using differential evolution algorithm

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2017年第10期42卷 1705-1715页

作者： Beskirli, Mehmet Hakli, Huseyin Kodaz, Halife Selcuk Univ Dept Comp Engn TR-42075 Konya Turkey

The energy demand estimation commands great importance for both developing and developed countries in terms of the economy and country resources. In this study, the differential evolution algorithm ( DE) was used to forecast the long-term energy demand in Turkey. In addition to being employed for solving regular optimization problems, DE is also a global, meta-heuristic algorithm that enables fast, reliable and operative stochastic searches based on population. Considering the correlation between the increase in certain economic indicators in Turkey and the increase of energy consumption, two equations were used-one applying the linear form and the other the quadratic form. Turkey's long-term energy demand from 2012 to 2031 was estimated through the DE method in three different scenarios and in terms of the gross domestic product, import, export and population. To prove the success of the DE method in addressing the energy demand problem, the DE method was compared to other methods found in the literature. Results showed that the proposed DE method was more successful than the other methods. Furthermore, the future projections of energy demand obtained using the proposed method were compared to the indicators of energy demand estimated and observed by the Ministry of Energy and Natural Resources.

关键词： differential evolution algorithm optimization energy demand estimation Turkey

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Optimization of a spectrum splitter using differential evolution algorithm for solar cell applications

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JOURNAL OF PHOTONICS FOR ENERGY 2015年第1期5卷

作者： Fan, Li Faryad, Muhammad Barber, Greg D. Mallouk, Thomas E. Monk, Peter B. Lakhtakia, Akhlesh Univ Delaware Dept Math Sci Newark DE 19716 USA Penn State Univ Dept Engn Sci & Mech University Pk PA 16802 USA Lahore Univ Management Sci Dept Phys DHA Lahore 54792 Pakistan Penn State Univ Penn State Inst Energy & Environm University Pk PA 16802 USA Penn State Univ Dept Chem University Pk PA 16802 USA

A spectrum splitter can be used to spatially multiplex different solar cells that have high efficiency in mutually exclusive parts of the solar spectrum. We investigated the use of a grating, comprising an array of dielectric cylinders embedded in a dielectric slab, for specularly transmitting one part of the solar spectrum while the other part is transmitted nonspecularly and the total reflectance is very low. A combination of (1) the rigorous coupled-wave approach for computing the reflection and transmission coefficients of the grating and (2) the differential evolution algorithm for optimizing the grating geometry and the refractive indices of dielectric materials was devised as a design tool. We used this tool to optimize two candidate gratings and obtained definite improvements to the initial guesses for the structural and constitutive parameters. Significant spectrum splitting can be achieved if the angle of incidence does not exceed 15 deg. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： solar spectrum splitting differential evolution algorithm optimization

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A hybrid differential evolution algorithm with estimation of distribution algorithm for reentrant hybrid flow shop scheduling problem

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NEURAL COMPUTING & APPLICATIONS 2018年第1期30卷 193-209页

作者： Zhou, Bing-hai Hu, Li-man Zhong, Zhen-yi Tongji Univ Sch Mech Engn Shanghai 201804 Peoples R China

This paper proposes a reentrant hybrid flow shop scheduling problem where inspection and repair operations are carried out as soon as a layer has completed fabrication. Firstly, a scheduling problem domain of reentrant hybrid flow shop is described, and then, a mathematical programming model is constructed with an objective of minimizing total weighted completion time. Then, a hybrid differential evolution (DE) algorithm with estimation of distribution algorithm using an ensemble model (eEDA), named DE-eEDA, is proposed to solve the problem. DE-eEDA incorporates the global statistical information collected from an ensemble probability model into DE. Finally, simulation experiments of different problem scales are carried out to analyze the proposed algorithm. Results indicate that the proposed algorithm can obtain satisfactory solutions within a short time.

关键词： Reentrant hybrid flow shop Scheduling differential evolution algorithm Estimation of distribution algorithm

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Application of a differential evolution algorithm in the Design of Public Lighting Installations Maximizing Energy Efficiency

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LEUKOS 2020年第3期16卷 217-227页

作者： Rabaza, Ovidio Gomez-Lorente, Daniel Pozo, Antonio M. Perez-Ocon, Francisco Univ Granada Dept Civil Engn Granada Spain Univ Granada Dept Opt Granada Spain

This article presents a differential evolution (DE) algorithm that can be used to plan public lighting for streets, roadways, and freeways and maximize the energy efficiency of the installation. The algorithm was applied to a model based on new relationships between the energy efficiency of street lighting systems and geometric parameters such as street width, luminaire height, and distance between poles. These relationships were derived from the regression analysis of a large sample of outputs. The results of this algorithm consisted of the luminaire arrangement (one-sided, two-sided staggered, and two-sided coupled), luminaire height, luminaire type, and pole spacing for the most energy-efficient installation. The input of the algorithm was the lighting class or illuminance level, street width, as well as various other luminaire parameters. When these results were compared with those of DIALux, the performance of this new method was found to be extremely satisfactory. Furthermore, the constraints applied guaranteed compliance with the recommendations of the International Commission on Illumination.

关键词： differential evolution algorithm energy efficiency optimization public lighting

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Hybrid differential evolution algorithm and genetic operator for multi-trip vehicle routing problem with backhauls and heterogeneous fleet in the beverage logistics industry

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 146卷 106571-106571页

作者： Sethanan, Kanchana Jamrus, Thitipong Khon Kaen Univ Fac Engn Dept Ind Engn Res Unit Syst Modeling Ind Khon Kaen 40002 Thailand

Logistics is increasingly challenging because of increased competition and the uncertainty introduced by globalization. The drinks distribution system considered here uses glass bottles for soft drinks to deliver to all customers who need soft drinks in glass bottles, before making any pickups of empty glass bottles from clients to return to the company. This study aims at both an integer linear programming formulation and a novel hybrid differential evolution algorithm involving a genetic operator with fuzzy logic controller, for solving the multitrip vehicle routing problem with backhauls and a heterogeneous fleet. The objective function is to minimize total cost, which is related to distance travelled. For validation, we designed numerical experiments to compare the proposed approaches with LINGO computational software, using the conventional differential evolution algorithm and differential evolution with selected genetic operator and fuzzy logic controller in real settings. The experimental results demonstrate the practical viability of the proposed approaches.

关键词： Vehicle routing problem Backhauls Multiple trips differential evolution algorithm Genetic operator

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An Application of differential evolution algorithm-based Restricted Boltzmann Machine to Recommendation Systems

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JOURNAL OF INTERNET TECHNOLOGY 2020年第3期21卷 701-712页

作者： Kuo, R. J. Chen, J. T. Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei Taiwan Chunghwa Telecom Co Ltd Dept Big Data Taipei Taiwan

Due to growth of electronic commerce, currently, many customers prefer to buying products from the internet. Thus, recommendation system, like restricted Boltzmann machine (RBM), has become a good technique to recommend the right product to the potential customer. This can dramatically increase the customer loyalty. However, it is necessary to determine some parameters for RBM and enhance its computation performance. Therefore, this study intends to propose a hybrid algorithm which combines the cluster-based restricted Boltzmann machine (CRBM) with differential evolution (DE) algorithm to optimize the RBM's parameters for collaborative filtering. The CRBM applies a clustering algorithm to determine the size and elements for each mini-batch gradient descent method for the RBM. The proposed DE-based CRBM algorithm is validated using four benchmark datasets. The results are compared with those of batch RBM, mini-batch RBM, clustering RBM, PSO-based and GA-based clustering RBM. The experimental results reveal that optimizing the RBM's parameters using metaheuristic can obtain the better result. It also show that the proposed DE-based CRBM algorithm performs better than GA-based and PSO-based CRBM algorithms.

关键词： Recommendation systems Collaborative filtering Restricted Boltzmann machine K-means algorithm differential evolution algorithm

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An efficient method for structural damage detection using a differential evolution algorithm-based optimisation approach

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CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS 2015年第3期32卷 230-250页

作者： Seyedpoor, S. M. Shahbandeh, S. Yazdanpanah, O. Shomal Univ Dept Civil Engn Amol Iran

An efficient method employing the differential evolution algorithm (DEA) as an optimisation solver is presented here to identify the multiple damage cases of structural systems. Natural frequency changes of a structure are considered as a criterion for damage occurrence. The structural damage detection problem is first transformed into a standard optimisation problem dealing with continuous variables, and then the DEA is utilised to solve the optimisation problem for finding the site and extent of structural damage. In order to assess the performance of the proposed method for structural damage identification, some illustrative examples are numerically tested, considering also measurement noise. All the numerical results demonstrate the effectiveness of the proposed method for accurately determining the site and extent of multiple-structural damage. Also, the performance of the DEA for damage detection compared to the standard particle swarm optimisation is confirmed by a test example.

关键词： structural damage detection optimisation method differential evolution algorithm measurement noise

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