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Selection of optimized features and weights on face-iris fusion using distance images

COMPUTER VISION AND IMAGE UNDERSTANDING 2015年 137卷 63-75页

作者： Eskandari, Maryam Toygar, Onsen Hasan Kalyoncu Univ Dept Comp Engn Gaziantep Turkey Eastern Mediterranean Univ Dept Comp Engn TR-10 Northern Cyprus Mersin Turkey

The focus of this paper is on proposing new schemes based on score level and feature level fusion to fuse face and iris modalities by employing several global and local feature extraction methods in order to effectively code face and iris modalities. The proposed schemes are examined using different techniques at matching score level and feature level fusion on CASIA Iris Distance database, Print Attack face database, Replay Attack face database and IIIT-Delhi Contact Lens iris database. The proposed schemes involve the consideration of Particle Swarm Optimization (PSO) and backtracking search algorithm (BSA) in order to select optimized features and weights to achieve robust recognition system by reducing the number of features in feature level fusion of the multimodal biometric system and optimizing the weights assigned to the face-iris multimodal biometric system scores in score level fusion step. Additionally, in order to improve face and iris recognition systems and subsequently the recognition of multimodal face-iris biometric system, the proposed methods attempt to correct and align the location of both eyes by measuring the iris rotation angle. Demonstration of the results based on both identification and verification rates clarifies that the proposed fusion schemes obtain a significant improvement over unimodal and other multimodal methods implemented in this study. Furthermore, the robustness of the proposed multimodal schemes is demonstrated against spoof attacks on several face and iris spoofing datasets. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Multimodal biometrics Particle Swarm Optimization backtracking search algorithm Information fusion Spoof attacks

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An image processing algorithm to estimate the melt fraction and energy storage of a PCM enclosed in a spherical capsule

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INTERNATIONAL JOURNAL OF ENERGY REsearch 2019年第10期43卷 5535-5547页

作者： Maheswararao, Uma G. Majumadar, Arpan Niphadkar, Tejas Krishna, Jaya D. Natl Inst Technol Warangal Dept Mech Engn Warangal Andhra Pradesh India Natl Inst Technol Warangal Dept Elect & Elect Engn Warangal Andhra Pradesh India

The experimental investigation of the melting behavior of a phase change material (PCM) inside a spherical container is reported. PCM considered for the study is lauric acid whose melting point is about 43 degrees C. Unconstrained melting experiments are carried out at two different temperatures, ie, at 60 degrees C and 80 degrees C. The initial temperature of the PCM is taken as 30 degrees C. To carry out a detailed analysis of the heat transfer, the transient variations in the melt fraction and amount of energy stored are derived. In order to estimate the liquid/solid volumes, a novel image processing technique is developed. In this approach, a circle-fitting algorithm is employed to obtain the amount of PCM melted inside a spherical container. The total instantaneous amount of heat transport to the PCM is measured with an uncertainty of about 6.1%. The results obtained by the introduced circle-fitting algorithm have been compared qualitatively and quantitatively with the solid modeling method. The present technique could capture the asymmetric behavior of the solid PCM. The experimental findings show that the rate of melt fraction is high at the beginning of the experiment due to a larger area of contact between the spherical container and solid PCM. Further, parametric analysis has been performed and reported in terms of Fourier, Stefan, and Grashof numbers.

关键词： backtracking search algorithm image processing technique melt fraction phase change unconstrained melting

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An Efficient Framework for Short-Term Electricity Price Forecasting in Deregulated Power Market

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IEEE ACCESS 2024年 12卷 43674-43690页

作者： Pourdaryaei, Alireza Mohammadi, Mohammad Muhammad, Munir Azam Bin Fakhrul Islam, Junaid Karimi, Mazaher Shahriari, Amidaddin Shiraz Univ Sch Elect & Comp Engn Dept Power & Control Shiraz *** Iran Univ Hormozgan Dept Elect & Comp Engn Bandar Abbas *** Iran Iqra Univ Dept Elect Engn Main Campus Karachi 75300 Pakistan Univ Malaya Fac Engn Dept Elect Engn Kuala Lumpur 50603 Malaysia Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Islamic Azad Univ Dept Elect Engn South Tehran Branch Tehran *** Iran

It is widely acknowledged that electricity price forecasting become an essential factor in operational activities, planning, and scheduling for the participant in the price-setting market, nowadays. Nevertheless, electricity price became a complex signal due to its non-stationary, non-linearity, and time-variant behavior. Consequently, a variety of artificial intelligence techniques are proposed to provide an efficient method for short-term electricity price forecasting. backtracking search algorithm as the recent augmentation of optimization technique, yield the potential of searching a closed-form solution in mathematical modeling with a higher probability, obviating the necessity to comprehend the correlations between variables. Concurrently, this study also developed a feature selection technique, to select the input variables subsets that have a substantial implication on forecasting of electricity price, based on a combination of mutual information and support vector machine. For the verification of simulation results, actual data sets from the Ontario energy market in the year 2020 covering various weather seasons are acquired. Finally, the obtained results demonstrate the feasibility of the proposed strategy through improved preciseness in comparison with the distinctive methods.

关键词： backtracking search algorithm electricity market electricity price forecasting feature selection support vector machine

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Comparative study between different optimisation techniques for finding precise switching angle for SHE-PWM of three-phase seven-level cascaded H-bridge inverter

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IET POWER ELECTRONICS 2018年第3期11卷 600-609页

作者： Kundu, Sourabh Burman, Arka Deb Giri, Santu K. Mukherjee, Sarbani Banerjee, Subrata Natl Inst Technol NIT Durgapur Dept Elect Engn Durgapur 713209 India CSIR Cent Mech Engn Res Inst SET Grp Durgapur 713209 India

Selective harmonic elimination pulse-width modulation (SHE-PWM) works at low-frequency switching, which reduces switching losses, device stress, and increases energy conversion efficiency. So, it can be an effective control strategy for multilevel inverter working on medium-voltage, high-power industrial energy conversion application. It provides desired output voltage by retaining the requested fundamental component as well as eliminating some low-order harmonics. The application of SHE-PWM in industries is having an influence on precise solvability of complex and non-linear equations. This study presents two recently reported optimisation techniques, namely backtracking search algorithm and differential search algorithm (DSA) for obtaining a more accurate solution of the harmonics elimination problem. The superiority of the proposed optimisation algorithms over the well known ancient algorithm such as genetic algorithm, BEE algorithm and particle swarm optimisation have been established by a comparative study with respect to the possibility of attaining global minima, the rank of convergence rate, and inverter performance analysis. Simulation and experimental results validate the efficacy of the DSA optimisation technique for calculating more precise switching angles that totally eliminate 5th- and 7th-order harmonics with fulfilling the requested fundamental component.

关键词： PWM invertors switching convertors harmonics suppression search problems genetic algorithms particle swarm optimisation SHE-PWM three-phase seven-level cascaded H-bridge inverter selective harmonic elimination pulse-width modulation multilevel inverter medium-voltage high-power industrial energy conversion application energy conversion efficiency low-order harmonic elimination complex equation nonlinear equation backtracking search algorithm DSA differential search algorithm genetic algorithm BEE algorithm particle swarm optimisation 5th-order harmonic elimination 7th-order harmonic elimination

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Bio-inspired Active System Identification: a Cyber-Physical Intelligence Attack in Networked Control Systems

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MOBILE NETWORKS & APPLICATIONS 2020年第5期25卷 1944-1957页

作者： de Sa, Alan Oliveira Carmo, Luiz F. R. da C. Machado, Raphael C. S. Brazilian Navy Admiral Wandenkolk Instruct Ctr Rio De Janeiro Brazil Univ Fed Rio de Janeiro Inst Math NCE Rio De Janeiro Brazil Natl Inst Metrol Qual & Technol Rio De Janeiro Brazil Rio de Janeiro Fed Ctr Technol Educ Rio De Janeiro Brazil

From the point of view of the control theory, the literature indicates that stealthy and accurate cyber-physical attacks on Networked Control System (NCS) must be planned based on an accurate knowledge about the model of the attacked system. However, most literature about these attacks does not indicate how such knowledge is obtained by the attacker. So, to fill this hiatus, an Active System Identification attack is proposed in this paper, where the attacker injects data on the NCS to learn about its model. The attack is implemented based on two bio-inspired metaheuristics: backtracking search Optimization algorithm (BSA) and Particle Swarm Optimization (PSO). To improve the accuracy of the estimated models, a statistical refinement is proposed for the outcomes of the two optimization algorithms. Additionally, a set of data injection attacks are shown in order to demonstrate the capability of the proposed attack in supporting the design of other sophisticated attacks. The results indicate a better performance of the BSA-based attacks, especially when the captured signals contain white Gaussian noise. The goal of this paper is to demonstrate the degree of accuracy that this System Identification attack may achieve, highlighting the potential impacts and encouraging the research of possible countermeasures.

关键词： Security Cyber-physical systems Networked control systems System identification backtracking search algorithm Particle swarm optimization

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Urban Water Demand Prediction for a City That Suffers from Climate Change and Population Growth: Gauteng Province Case Study

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WATER 2020年第7期12卷 1885页

作者： Zubaidi, Salah L. Ortega-Martorell, Sandra Al-Bugharbee, Hussein Olier, Ivan Hashim, Khalid S. Gharghan, Sadik Kamel Kot, Patryk Al-Khaddar, Rafid Wasit Univ Dept Civil Engn Wasit 52001 Iraq Liverpool John Moores Univ Dept Appl Math Liverpool L3 3AF Merseyside England Wasit Univ Dept Mech Engn Wasit 52001 Iraq Liverpool John Moores Univ Built Environm & Sustainable Technol BEST Res Ins Liverpool L3 3AF Merseyside England Babylon Univ Dept Environm Engn Babylon 51001 Iraq Middle Tech Univ Elect Engn Tech Coll Dept Med Instrumentat Tech Engn Baghdad 10022 Iraq

The proper management of a municipal water system is essential to sustain cities and support the water security of societies. Urban water estimating has always been a challenging task for managers of water utilities and policymakers. This paper applies a novel methodology that includes data pre-processing and an Artificial Neural Network (ANN) optimized with the backtracking search algorithm (BSA-ANN) to estimate monthly water demand in relation to previous water consumption. Historical data of monthly water consumption in the Gauteng Province, South Africa, for the period 2007-2016, were selected for the creation and evaluation of the methodology. Data pre-processing techniques played a crucial role in the enhancing of the quality of the data before creating the prediction model. The BSA-ANN model yielded the best result with a root mean square error and a coefficient of efficiency of 0.0099 mega liters and 0.979, respectively. Moreover, it proved more efficient and reliable than the Crow search algorithm (CSA-ANN), based on the scale of error. Overall, this paper presents a new application for the hybrid model BSA-ANN that can be successfully used to predict water demand with high accuracy, in a city that heavily suffers from the impact of climate change and population growth.

关键词： artificial neural network backtracking search algorithm municipal water demand climate change population growth

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Using Constraint Satisfaction Problem approach to solve human resource allocation problems in cooperative health services

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EXPERT SYSTEMS WITH APPLICATIONS 2012年第1期39卷 385-394页

作者： Fernandes Costa Filho, Cicero Ferreira Rivera Rocha, Dayse Aparecida Fernandes Costa, Many Guimaraes de Albuquerque Pereira, Wagner Coelho Univ Fed Amazonas Ctr Tecnol Eletron & Informacao BR-69077000 Manaus Amazonas Brazil Fundacao Ctr Anal Pesquisa & Inovacao Tecnol FUCA Manaus Amazonas Brazil COPPE UFRJ Programa Engn Biomed BR-21941972 Rio De Janeiro Brazil

In developing countries, the increasing utilization of health services, due to a great life expectancy, is followed by a reduction in incomes from the public health system and from private insurance companies, to the payment of medical procedures. Beyond this scenery, it is mandatory an effective hospital cost control though the utilization of planning tools. This work is intended to contribute to the reduction of hospital costs, proposing a new tool for planning human resources utilization in hospital plants. Specifically, it is proposed a new tool for human resources allocation in health units. The solution to the allocation problem uses the CSP technique (Constraint Satisfaction Problem) associated with the backtracking search algorithm. With the objective of enhancing the backtracking search algorithm performance a new heuristics is proposed. Through some simulations the performance of the proposed heuristics is compared to the other heuristics previously published in literature: remaining minimum values, forward checking and grade heuristics. Another important contribution of this work is the mathematical modeling of the constraints, that could be unary, multiple, numeric and implicit constraints. In the results it is presented a case study of a human resource allocation in a cooperative health service. Based on the results, it is proposed that for a real allocation problems solution, the best approach is to combine the remaining minimum values heuristics with the grade heuristics, to select the best unit allocation to be filled, and then use the proposed heuristic to select the best physician to the chosen unit allocation. This association shows a satisfactory result for the human resource allocation problem of the case study, with an algorithm convergence time of 46.7 min with no backtracks. The same problem when manually resolved took about more than 50 h. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Human resource allocation Cooperative services Heuristics Constraint Satisfaction Problem backtracking search algorithm

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A procedure for the size, shape and topology optimization of transmission line tower structures

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ENGINEERING STRUCTURES 2016年 111卷 162-184页

作者： de Souza, Rafael Rodrigues Fadel Miguel, Leandro Fleck Lopez, Rafael Holdorf Fadel Miguel, Leticia Fleck Torii, Andre Jacomel Univ Fed Santa Catarina Dept Civil Engn CORE Florianopolis SC Brazil Univ Fed Rio Grande do Sul Dept Mech Engn Porto Alegre RS Brazil Univ Fed Paraiba Dept Sci Comp BR-58059900 Joao Pessoa Paraiba Brazil

This paper presents a methodology for topology optimization of transmission line towers. In this approach, the structure is divided in main modules, which can assume different pre-established topologies (templates). A general rule for the templates creation is also presented, which is based in terms of the design practice and feasibility of prototype testing. Thus, these allow that the optimal solution has an important characteristic of direct industrial application. Furthermore, during the optimization process the size and shape of the structure are optimized simultaneously to the topology choice. For numerical examples, two structures were assessed. The first one is a transmission line tower studied in CIGRE (2009). Eight different load cases were considered. The second one is a single circuit, self-supported 115 kV transmission line tower. The structure was subjected to a cable conductor rupture scenario and a wind load hypothesis. In both examples the constraints from the ASCE 10-97 (2000) were applied. Due to the non-convex nature of the problem and to the presence of discrete variables in the procedure, the optimization was conducted through the Firefly algorithm (FA) and the backtracking search algorithm (BSA), which are two modem heuristic algorithms. The results for the size, size and shape, and size, shape and topology optimization are presented and discussed, as well as an analysis of the performance of the algorithms. It is shown that the proposed scheme is able to reduce up to 6.4% of the structural weight, when compared to a classical size optimization procedure on original structures. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Structural optimization Transmission line towers Industrial application Firefly algorithm backtracking search algorithm

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Positioning multiple optical network units in fiber-wireless networks: An efficient hybrid K-harmonic means clustering approach

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OPTICAL FIBER TECHNOLOGY 2024年 84卷

作者： Emami, Hojjat Pashazadeh, Saeid Univ Bonab Dept Comp Engn Bonab Iran Univ Tabriz Fac Elect & Comp Engn Dept IT Tabriz Iran

Wireless-optical broadband access network (WOBAN) or fiber-wireless (FiWi) is a robust and cost-effective solution to provide high bandwidth network connectivity to mobile subscribers. Optical network unit (ONU) placement is a topological optimization problem that plays a vital role in effective deployment of FiWi network. Recently, some artificial intelligence-based approaches for positioning ONUs were proposed and generated promising results. However, the reported performance in the literature is far from the ideal state. This issue emphasizes the necessity of introducing new placement methods or improving the performance of existing methods. This paper presents a hybrid clustering algorithm for finding the optimal position of multiple ONUs. The proposed backtracking K-harmonic means (BKHM) is an integration of K-harmonic means (KHM) and a backtracking search algorithm (BSA). BKHM not only efficiently specifies the optimal positions of ONUs but also significantly decreases the implementation cost. To demonstrate the performance of the BKHM, we evaluate it on well-known placement benchmarks compared with BSA, KHM, whale optimization algorithm (WOA), enhanced backtracking search (EBS), harris hawks optimization (HHO), and chaotic local search-based levy flight distribution (CLF) algorithms. The experimental results and statistical analysis proved that the proposed BKHM algorithm outperformed its counterparts on most benchmarks in terms of cost optimization, convergence accuracy, and solution quality.

关键词： backtracking search algorithm Clustering Fiber-wireless network K-harmonic means Optical network unit placement

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A novel inverse modeling control for piezo positioning stage

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2018年第12期32卷 5875-5888页

作者： To Xuan Dinh Nguyen Phi Luan Kyoung Kwan Ahn Univ Ulsan Sch Mech & Automot Engn Ulsan South Korea T Robot Co Ltd Gyeonggi Do South Korea

This paper focuses on the application of a novel inverse nonlinear autoregressive with exogenous input (NARX) structure and a fuzzy inference system on position control of a piezo positioning stage (PPS) system. The highly relationship between input voltage and output displacement is thoroughly modeled by using the inverse fuzzy NARX model-based identification process with the experiment training data. The unknown parameters of the proposed NARX fuzzy model was obtained base on a hybridization between backtracking search algorithm and gradient descent technique. A combination between fuzzy propositional-integral-derivative controller and inverse modeling feedforward controller was then applied to control PPS with several challenged working condition. The results show efficiency of the proposed method for the PPS system in terms of high tracking precision and excellent dynamic performance.

关键词： Piezo positioning stage backtracking search algorithm Inverse modeling Nonlinear auto regressive exogenous

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