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Improved binary artificial bee colony algorithm Research Articles

Rafet Durgut,rafetdurgut@karabuk.edu.tr

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 8, Pages 1080-1091 doi: 10.1631/FITEE.2000239

Abstract: The (ABC) algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’ food search behavior. Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space, modification is required to apply it to problems. In this study, we modify the ABC algorithm to solve problems and name it the improved binary ABC (IbinABC). The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables. Therefore, we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability. We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature. For comparison, we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem. Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness. The source code of the algorithm is available at https://github.com/rafetdurgut/ibinABC.

Keywords：人工蜂群；二进制优化；无容量限制的设施选址位置问题（UFLP）

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Reversible binary subtractor design using quantumdot-cellular automata Article

Jadav Chandra DAS, Debashis DE

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 9, Pages 1416-1429 doi: 10.1631/FITEE.1600999

Abstract: In the field of nanotechnology, quantum dot-cellular automata(QCA) is the promising archetype that can provide an alternative solutionto conventional complementary metal oxide semiconductor (CMOS) circuit.QCA has high device density, high operating speed, and extremely lowpower consumption. Reversible logic has widespread applications inQCA. Researchers have explored several designs of QCA-based reversiblelogic circuits, but still not much work has been reported on QCA-basedreversible binary subtractors. The low power dissipation and highcircuit density of QCA pledge the energy-efficient design of logiccircuit at a nano-scale level. However, the necessity of too manylogic gates and detrimental garbage outputs may limit the functionalityof a QCA-based logic circuit. In this paper we describethe design and implementation of a DG gate in QCA. The universal natureof the DG gate has been established. The QCA building block of theDG gate is used to achieve new reversible binary subtractors. Theproposed reversible subtractors have low quantum cost and garbageoutputs compared to the existing reversible subtractors. The proposedcircuits are designed and simulated using QCA Designer-2.0.3.

Keywords： Quantum dot-cellular automata (QCA) Reversible logic DG gate Binary subtractor Quantum cost

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Competitive binary multi-objective grey wolf optimizer for fast compact antenna topology optimization Research Article

Jian DONG, Xia YUAN, Meng WANG

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 9, Pages 1390-1406 doi: 10.1631/FITEE.2100420

Abstract: We propose a competitive binary (CBMOGWO) to reduce the heavy computational burden of conventional multi-objective problems. This method introduces a population competition mechanism to reduce the burden of electromagnetic (EM) simulation and achieve appropriate fitness values. Furthermore, we introduce a function of cosine oscillation to improve the linear convergence factor of the original binary (BMOGWO) to achieve a good balance between exploration and exploitation. Then, the optimization performance of CBMOGWO is verified on 12 standard multi-objective test problems (MOTPs) and four multi-objective knapsack problems (MOKPs) by comparison with the original BMOGWO and the traditional binary multi-objective particle swarm optimization (BMOPSO). Finally, the effectiveness of our method in reducing the computational cost is validated by an example of a compact high-isolation dual-band multiple-input multiple-output (MIMO) antenna with high-dimensional mixed design variables and multiple objectives. The experimental results show that CBMOGWO reduces nearly half of the computational cost compared with traditional methods, which indicates that our method is highly efficient for complex problems. It provides new ideas for exploring new and unexpected antenna structures based on multi-objective evolutionary algorithms (MOEAs) in a flexible and efficient manner.

Keywords： Antenna topology optimization Multi-objective grey wolf optimizer High-dimensional mixed variables Fast design

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Modified Binary Artificial Bee Colony Algorithm forMultidimensional Knapsack Problem

Wang Zhigang,Xia Huiming

Strategic Study of CAE 2014, Volume 16, Issue 8, Pages 106-112

Abstract:

The binary artificial bee colony algorithm has the shortcomings of slower convergence speed and falling into local optimum easily. According to the defects, a modified binary artificial bee colony algorithm is proposed. The algorithm redesign neighborhood search formula in artificial bee colony algorithm, the probability of the food position depends on the Bayes formula. The modified algorithm was used for solving multidimensional knapsack problem, during the evolution process, it uses the greedy algorithm repairs the infeasible solution and rectify knapsack resources with insufficient use. The simulation results show the feasibility and effectiveness of the proposed algorithm.

Keywords： artificial bee colony algorithm multidimensional knapsack problem greedy algorithm combinatorial optimization

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Deep learning compact binary codes for fingerprint indexing None

Chao-chao BAI, Wei-qiang WANG, Tong ZHAO, Ru-xin WANG, Ming-qiang LI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 9, Pages 1112-1123 doi: 10.1631/FITEE.1700420

Abstract:

With the rapid growth in fingerprint databases, it has become necessary to develop excellent fingerprint indexing to achieve efficiency and accuracy. Fingerprint indexing has been widely studied with real-valued features, but few studies focus on binary feature representation, which is more suitable to identify fingerprints efficiently in large-scale fingerprint databases. In this study, we propose a deep compact binary minutia cylinder code (DCBMCC) as an effective and discriminative feature representation for fingerprint indexing. Specifically, the minutia cylinder code (MCC), as the state-of-the-art fingerprint representation, is analyzed and its shortcomings are revealed. Accordingly, we propose a novel fingerprint indexing method based on deep neural networks to learn DCBMCC. Our novel network restricts the penultimate layer to directly output binary codes. Moreover, we incorporate independence, balance, quantization-loss-minimum, and similarity-preservation properties in this learning process. Eventually, a multi-index hashing (MIH) based fingerprint indexing scheme further speeds up the exact search in the Hamming space by building multiple hash tables on binary code substrings. Furthermore, numerous experiments on public databases show that the proposed approach is an outstanding fingerprint indexing method since it has an extremely small error rate with a very low penetration rate.

Keywords： Fingerprint indexing Minutia cylinder code Deep neural network Multi-index hashing

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应用完备集合固有时间尺度分解和混合差分进化和粒子群算法优化的最小二乘支持向量机对柴油机进行故障诊断 Article

俊红张,昱刘

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 2, Pages 272-286 doi: 10.1631/FITEE.1500337

Abstract: 针对固有时间尺度分解算法的模态混叠问题和最小二乘支持向量机的参数优化问题，本文提出了一种新的基于完备集合固有时间尺度分解和混合差分进化和粒子群算法优化最小二乘支持向量机的柴油机故障诊断方法。最后，提出了混合差分进化和粒子群算法对最小二乘支持向量机的参数进行优化的方法，并通过将故障特征输入训练好的最小二乘支持向量机模型实现故障诊断。

Keywords：柴油机；故障诊断；完备集合固有时间尺度分解；最小二乘支持向量机；混合差分进化和粒子群优化算法

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Reliability Optimization Design for Coil Tube-spring

Zhang Yimin,He Xiangdong,Wen Bangchun

Strategic Study of CAE 2002, Volume 4, Issue 5, Pages 71-74

Abstract:

Techniques from the second moment method and reliability optimization design method are employed to present the practical and effective method for the reliability optimization design for coil tube-spring on the condition of known probabilistic characteristics of basic random variables. The respective program can be used to obtain the reliability optimization design information of coil tube-spring accurately and quickly.

Keywords： coil tube-spring reliability optimization design second moment method

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Binary Optics Used in High Power Laser Shaping

Jin Guopan,Tan Qiaofeng,Yan Yingbai,Wu Minxian

Strategic Study of CAE 2000, Volume 2, Issue 6, Pages 27-32

Abstract:

The principle of binary optics used for beam shaping is introduced. On the basis of the analysis of GS and YG algorithms, three algorithms are developed for phase design of the Binary Optical Element (BOE), including Global/local united searching algorithm (GLUSA), hybrid algorithm combining Hill-climbing with Simulated Annealing and its multi-resolution algorithm. For example, the BOE obtaining uniform focused spot for Inertial Confinement Fusion (ICF) is designed by the above algorithms. The simulated results show that fine phase structure and good characters of the focused spot are realized by using the hybrid algorithm. A continuous phase plate is manufactured with a rotating hollowed-out mask. The intensity distribution of the focused spot is measured by a common CCD and multi-attenuators with which the measurement dynamic range is increased .The experimental results after data processing show that the focused spot with steep edge, low side lobe, high light efficiency and fair uniformity of the main lobe without sharp peak at the zero order is obtained.

Keywords： beam shaping binary optics phase element optimization algorithm

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Colocated MIMO radar waveform-design based on two-step optimizations in spatial and spectral domains Article

Yu-xi WANG, Guo-ce HUANG, Wei LI, Jin-liang LI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7, Pages 1021-1032 doi: 10.1631/FITEE.1601726

Abstract: We propose an efficient colocated multiple-input multiple-output radar waveform-design method based on two-step optimizations in the spatial and spectral domains. First, a minimum integrated side-lobe level strategy is adopted to obtain the desired beam pattern with spatial nulling. By recovering the hidden convexity of the resulting fractional quadratically constrained quadratic programming non-convex problem, the global optimal solution can be achieved in polynomial time through a semi- definite relaxation followed by spectral factorization. Second, with the transmit waveforms obtained via spatial optimization, a phase changing diagonal matrix is introduced and optimized via power method-like iterations. Without influencing the shape of the optimized beam pattern, the transmit waveforms are further optimized in the spectral domain, and the desired spectral nulling is formed to avoid radar interference on the overlaid licensed radiators. Finally, the superior performance of the proposed method is demonstrated via numerical results and comparisons with other approaches to waveform design.

Keywords： Multiple-input multiple-output (MIMO) radar Waveform design Spectral factorization Fractional quadratically constrained quadratic programming (QCQP)

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Prediction of vibration response of powerhouse structures based on LS-SVM optimized by PSO

Lian Jijian,He Longjun,Wang Haijun

Strategic Study of CAE 2011, Volume 13, Issue 12, Pages 45-50

Abstract:

The vibration of powerhouse structures is mainly induced by hydraulics factors, mechanical and electromagnetic factors of the generating unit. It nonlinearly couples with the generating unit. Based on prototype observation data of Ertan Hydropower Station, the paper analyzes the coupling effect between vibration of units and powerhouse,and then the vibration response forecasting model of the powerhouse is built based on LS-SVM optimized by particle swarm optimization algorithm, and the prediction results are coincide with the observed data. Further, the paper introduces the running water head as an input divisor into the intelligent prediction model while the forecasting range is extended, and the result is satisfactory.

Keywords： powerhouse coupled vibration particle swarm optimization algorithm least squares support vector machines response prediction

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Performance Optimization Analysis of 2D - OOSC Codeword for OCDMA System

Li Chuanqi,Sun Xiaohan,Zhang Mingde,Ding Dong

Strategic Study of CAE 2003, Volume 5, Issue 4, Pages 50-54

Abstract:

The scheme of 2-dimensions optical orthogonal square codes (2D - OOSC) in optical code-division multiple-access (OCDMA) networks is given in this paper. The influence of coding parameters to the performance of the system is mainly discussed. It is proved that the relativity of the codeword satisfies the system requirement, and the system BER based on multiple user interference is ascertained. The results indicate that the number of simultaneous users that can be contained in this system will be much larger than that in the system with ID-OOC under the same conditions, the total transmitting capacity of the system will reach the level of Tb/s, and the performance of 2D — OOSC system will be largely enhanced, especially under the heavy transmitting traffic.

Keywords： optical code division multiple access (OCDMA) 2-dimensions optical orthogonal square codes (2D-OOSC) multi-users interfering (MUI) based bit-error-ratio (BER)

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Flight control for air-breathing hypersonic vehicles using linear quadratic regulator design based on stochastic robustness analysis Article

Lin CAO, Shuo TANG, Dong ZHANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7, Pages 882-897 doi: 10.1631/FITEE.1601363

Abstract: The flight dynamics model of air-breathing hypersonic vehicles (AHVs) is highly nonlinear and multivariable cou-pling, and includes inertial uncertainties and external disturbances that require strong, robust, and high-accuracy controllers. In this paper, we propose a linear-quadratic regulator (LQR) design method based on stochastic robustness analysis for the longitudinal dynamics of AHVs. First, input/output feedback linearization is used to design LQRs. Second, subject to various system parameter uncertainties, system robustness is characterized by the probability of stability and desired performance. Then, the mapping rela-tionship between system robustness and LQR parameters is established. Particularly, to maximize system robustness, a novel hybrid particle swarm optimization algorithm is proposed to search for the optimal LQR parameters. During the search iteration, a Chernoff bound algorithm is applied to determine the finite sample size of Monte Carlo evaluation with the given probability levels. Finally, simulation results show that the optimization algorithm can effectively find the optimal solution to the LQR parameters.

Keywords： Air-breathing hypersonic vehicles (AHVs) Stochastic robustness analysis Linear-quadratic regulator (LQR) Particle swarm optimization (PSO) Improved hybrid PSO algorithm

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Design and analysis of carbon nanotube FET based quaternary full adders Article

Mohammad Hossein MOAIYERI,Shima SEDIGHIANI,Fazel SHARIFI,Keivan NAVI

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 10, Pages 1056-1066 doi: 10.1631/FITEE.1500214

Abstract: CMOS binary logic is limited by short channel effects, power density, and interconnection restrictions. The effective solution is non-silicon multiple-valued logic (MVL) computing. This study presents two high-performance quaternary full adder cells based on carbon nanotube field effect transistors (CNTFETs). The proposed designs use the unique properties of CNTFETs such as achieving a desired threshold voltage by adjusting the carbon nanotube diameters and having the same mobility as p-type and n-type devices. The proposed circuits were simulated under various test conditions using the Synopsys HSPICE simulator with the 32 nm Stanford comprehensive CNTFET model. The proposed designs have on average 32% lower delay, 68% average power, 83% energy consumption, and 77% static power compared to current state-of-the-art quaternary full adders. Simulation results indicated that the proposed designs are robust against process, voltage, and temperature variations, and are noise tolerant.

Keywords： Nanoelectronics Carbon nanotube FET Multiple-valued logic Quaternary logic

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Optimization of formation for multi-agent systems based on LQR

Chang-bin Yu, Yin-qiu Wang, Jin-liang Shao,brad.yu@anu.edu.au,wh6508@gmail.com,jinliangshao@126.com

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 2, Pages 96-109 doi: 10.1631/FITEE.1500490

Abstract: In this paper, three optimal linear algorithms are proposed for first-order linear from a perspective with cost functions consisting of both interaction energy cost and individual energy cost, because both the collective object (such as formation or consensus) and the individual goal of each agent are very important for the overall system. First, we propose the optimal formation algorithm for first-order without initial physical couplings. The parameter matrix of the algorithm is the solution to an . It is shown that the matrix is the sum of a Laplacian matrix and a positive definite diagonal matrix. Next, for physically interconnected , the optimal formation algorithm is presented, and the corresponding parameter matrix is given from the solution to a group of quadratic equations with one unknown. Finally, if the communication topology between agents is fixed, the local feedback gain is obtained from the solution to a quadratic equation with one unknown. The equation is derived from the derivative of the cost function with respect to the local feedback gain. Numerical examples are provided to validate the effectiveness of the proposed approaches and to illustrate the geometrical performances of .

Keywords： Linear quadratic regulator (LQR) Formation control Algebraic Riccati equation (ARE) Optimal control Multi-agent systems

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Progress and Prospect of Semiconductor Silicon Wafers in China

Zhang Guohu, Xiao Qinghua, Ma Fei

Strategic Study of CAE 2023, Volume 25, Issue 1, Pages 68-78 doi: 10.15302/J-SSCAE-2023.01.002

Abstract:

Silicon wafers are fundamental materials for semiconductors. China's semiconductor silicon wafers are highly dependent on foreign trade. Enhancing the independent guarantee capability of silicon wafers is significant for improving the overall level of China’s semiconductor industry. This study focuses on the market-dominant 8-inch and 12-inch silicon wafers, analyzes the development status of the global semiconductor silicon wafer technologies and industry, and prospects the development trend of the industry. The study specifically focuses on the development status of China's semiconductor silicon wafer industry, and points out that the industry in China is currently facing critical developing opportunities considering the market demand, macro policies, supporting capacities, R&D investment, and other favorable factors; meanwhile, it still faces challenges. Furthermore, the following measures and suggestions are proposed: (1) further strengthening top-level design and macro planning, (2) strengthening policy implementation and sustainability, (3) supporting the coordinated development of the industrial chain, and (4) developing semiconductor silicon wafers for advanced processing of integrated circuits, hoping to provide a reference for the higher-quality development of China’s semiconductor silicon wafer industry.

Keywords： semiconductor silicon wafer 8 inches 12 inches industry synergy advanced processing