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6th International Conference on Geotechnics, Civil Engineering and Structures (CIGOS)

作者： Viet-Hung Truong Hoang-Anh Pham Van-Thuyet Ngo Minh-Phuong Nguyen Thuyloi Univ 175 TaySon Hanoi Vietnam Ha Noi Univ Civil Engn 55 GiaiPhong Rd Hanoi Vietnam

ISBN: (纸本)9789811671609;9789811671593

Metaheuristics have been increasingly applied in structural design optimization due to their efficiency in finding the global optimal solutions. Several metaheuristic techniques have been proposed for the optimal design of structures. However, the performance of each method depends on the characteristic of the considered problem. Moreover, many metaheuristics require different control parameters to be tuned for their effectiveness. In this paper, we present a parameter-free metaheuristic based on the rao algorithms to optimize steel frames. Direct analysis based on nonlinear inelastic analysis is utilized to capture the nonlinearity of material and structural geometry. The rao algorithm, which is enhanced by an effective scheme to skip unpromising candidates without performing time-consumed nonlinear inelastic analyses, is used as the optimizer for the optimization. A two-story space steel frame is studied to show the effectiveness of the proposed method.

关键词： Optimization rao algorithm Nonlinear inelastic analysis Advanced analysis Steel frame

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Optimization of Cropping Pattern for Karjan Reservoir, India, Using rao algorithm 4th

Optimization of Cropping Pattern for Karjan Reservoir, India...

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4th International Conference on Advanced Engineering Optimization Through Intelligent Techniques

作者： Patel, Abhishek Yadav, S. M. Waikhom, Sahita Yadav, Vipinkumar Dr S & SS Gandhy Engn Coll Dept Civil Engn Surat India SVITT Dept Civil Engn Surat India

ISBN: (纸本)9789819796618;9789819746545;9789819746538

Appropriate allocation of water resources is required for better yield of crop. One of the major left bank tributaries of Narmada River, India, is the Karjan River. The Karjan reservoir is a single purpose reservoir, meant for irrigation. The culturable command area of left bank main canal (LBMC) of Karjan reservoir is 425.1 km(2) and right bank main canal (RBMC) is 136.9 km(2). In the present study, an optimizing model is developed for maximizing net benefits for a crop area using rao-1 algorithm and compared with linear programming model. rao-1 algorithm only requires common controlling parameters such as population size and number of iterations and does not require any parameter specific to the algorithm. Two scenarios have been used in the present study. In the first case, net benefits are evaluated using existing cropping pattern, and in the second case, a cropping pattern has been proposed using LP and rao-1 models to maximize net benefits. The constraints like reservoir storage, water allocation, evaporation, and overflow have been considered for developing the optimization model. The finding shows that the cropping area should be increased for sugarcane, wheat, and Juvar crops to maximize net benefits. The outcome of rao-1 algorithm was compared with linear programming (LP) model and was observed to be better.

关键词： Reservoir operation Optimization Cropping pattern Linear programming rao algorithm

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Binary rao algorithm-Based Approach for Diagnosing Alzheimer's Disease 4th

Binary Rao Algorithm-Based Approach for Diagnosing Alzheimer...

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4th International Conference on Advanced Engineering Optimization Through Intelligent Techniques

作者： Chaudhuri, Abhilasha Mohdiwale, Samrudhi Sardar Vallabhbhai Natl Inst Technol Dept Comp Sci & Engn Surat Gujrat India Siksha O Anusandhan Univ Inst Tech Educ & Res Dept Comp Sci & Informat Technol Bhubaneswar Odisha India

ISBN: (纸本)9789819796618;9789819746545;9789819746538

Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions of people worldwide. It affects the patient's cognitive abilities such as judgment, memory, and learning abilities. Early and accurate diagnosis of AD is crucial for effective treatment and disease management. Researchers have created a dataset specially to detect AD based on handwriting. This dataset has 450 features. All of the features are not equally important. Therefore, to select the set of relevant features, feature selection techniques need to be introduced here which will improve the classifier performance. Taking the challenge of optimal feature selection for automatic diagnosis of AD on handwriting-based evaluation, this work uses the rao optimization algorithms (rao-1, rao-2, and rao-3). The algorithms have been modified to solve the problem of binary feature selection by introducing transfer function. The study uses the wrapper method of feature selection and classification accuracy used as the objective function which needs to be maximized. Significant improvement in the accuracy has been achieved by applying the rao optimization algorithm. The results obtained from the study are also compared with existing work on the dataset. Comparison with existing work also shows the better performance of wrapper method-based rao algorithm of feature selection for classification of patients with AD.

关键词： Alzheimer's disease Feature selection rao algorithm Classification

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Optimal Reactive Power Dispatch With Time-Varying Demand and Renewable Energy Uncertainty Using rao-3 algorithm

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IEEE ACCESS 2021年 9卷 23264-23283页

作者： Hassan, Mohamed H. Kamel, Salah El-Dabah, Mahmoud A. Khurshaid, Tahir Dominguez-Garcia, Jose Luis Aswan Univ Fac Engn Dept Elect Engn Aswan 81542 Egypt Al Azhar Univ Fac Engn Elect Engn Dept Cairo 11651 Egypt Yeungnam Univ Dept Elect Engn Gyongsan 38541 South Korea Catalonia Inst Energy Res IREC St Adria de Besos 08930 Spain

The appropriate control and management of reactive power is of great relevance in the electrical reliability, stability, and security of power grids. This issue is considered in order to increase system efficiency and to maintain voltage under the acceptable value range. In this regard, novel technologies as FACTS, renewable energies, among others, are varying conventional grid behavior leading to unexpected limit capacity reaching due to large reactive power flow. Thus, optimal planning of this must be considered. This paper proposes a new application for a simple and easy implementation optimization algorithm, called rao-3, to solve the constrained non-linear optimal reactive power dispatch problem. Moreover, the integration of solar and wind energy as the most applied technologies in electric power systems are exploited. Due to the continuous variation and the natural intermittence of wind speed and solar irradiance as well as load demand fluctuation, the uncertainties which have a global concern are investigated and considered in this paper. The proposed single-objective and multi-objective deterministic/stochastic optimal reactive power dispatch algorithms are validated using three standard test power systems, namely IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus. The simulation results show that the proposed optimal reactive power dispatch algorithms are superior compared with two recent algorithms (Artificial electric field algorithm (AEFA) and artificial Jellyfish Search (JS) algorithm) and other optimization algorithms used for solving the same problem.

关键词： Optimization Uncertainty Reactive power Wind speed Renewable energy sources Probability density function Generators Renewable energy uncertainty time-varying demand optimal reactive power dispatch (ORPD) rao algorithm backward reduction algorithm

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Optimal power flow solutions for normal and critical loading scenarios using hybrid rao-2 sine cosine algorithm

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COMPUTERS & ELECTRICAL ENGINEERING 2025年 123卷

作者： Mittal, Udit Nangia, Uma Jain, Narender Kumar Gupta, Saket Delhi Technol Univ Delhi 110042 India Delhi Technol Univ Dept Elect Engn Delhi 110042 India Bharati Vidyapeeths Coll Engn Dept Instrumentat & Control Engn New Delhi 110063 India

This study explores integrating a novel Hybrid rao-2 Sine Cosine algorithm (HRSCA) into power systems to address optimal power flow (OPF) challenges, particularly under high loading and contingency scenarios. HRSCA combines the Sine-Cosine algorithm's exploratory capabilities with the rao-2 algorithm's exploitative strengths, enhancing convergence speed and solution quality. It balances exploration and exploitation, ensuring diverse, optimal solutions that meet OPF constraints without added complexity. Rigorous testing on IEEE 30-bus and 118-bus systems demonstrates its robust performance and superiority over contemporary algorithms in standard OPF studies and scenarios like load growth and generator outages. HRSCA effectively lowers fuel costs and emissions, improves voltage stability, minimizes voltage deviations, and enhances load margin stability under operational stressors like faults. For example, in generator outage scenarios on the IEEE 30-bus system at a loading factor of 1.0932 p.u., it achieved a fuel cost of 1,021.6998 $/h, reflecting a marginal yet noteworthy 0.03 % improvement over the previously reported 1,022.0078 $/h. It also reduced power loss to 9.4336 MW, a notable 3.46 % improvement from 9.772 MW, with emission costs as low as 0.3726 ton/h and 0.3802 ton/h, respectively. For the IEEE 118-bus system, HRSCA minimized fuel costs to 129,088.63 $/h, a 1.62 % improvement over the base case of 131,220.52 $/h, outperforming many recent algorithms. These results highlight HRSCA's potential to enhance efficiency, stability, security, and environmental performance, even under critical conditions.

关键词： rao algorithm Sine cosine algorithm Security OPF Hybrid optimization Generator contingency Loadability

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Research on Fourier Transform Spectral Phase Correction algorithm Based on CTKB-NCM

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PHOTONICS 2025年第3期12卷 219-219页

作者： Wang, Xiong Yan, Chunhui Huo, Zimin Dai, Pengzhang Yao, Dong Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Changchun 130033 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China State Key Lab Dynam Opt Imaging & Measurement Changchun 130033 Peoples R China Aerosp Informat Technol Univ Sch Nav & Internet Things Jinan 250299 Peoples R China

In Fourier Transform Spectrometers, phase errors in spectral measurement induce distortion in reconstructed spectra. Existing phase correction algorithms demonstrate insufficient precision in addressing both linear phase and instrumental phase components, resulting in limited applications for the restored spectra in the field of precision measurement. This paper proposes an algorithm called the Cross-Teager-Kaiser psi B Energy Operator-Nonlinear Calibration Model (CTKB-NCM) for phase error correction. The algorithm first uses the cross-Teager-Kaiser psi B energy operator (CTKB) method to correct linear phase errors, then applies the Nonlinear Calibration Model (NCM) to solve for the instrument phase correction parameters at each wavenumber, and finally uses the instrument phase correction parameters to correct the residual phase after the linear phase error has been corrected. The rao algorithm is used to determine the optimal instrument phase correction parameters. Simulation experiments demonstrate that the CTKB-NCM method achieves an order-of-magnitude improvement in normalized reconstructed spectral accuracy for SO2 gas compared to the conventional Mertz method.

关键词： Fourier Transform Spectroscopy phase correction algorithms instrument phase cross Teager-Kaiser energy operator rao algorithm

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Frequency Regulation on an Interconnected Power System With Fractional PID Controllers Optimized Using rao algorithms

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2022年第13期50卷 683-695页

作者： Sony, M. G. Thomas, Lithin P. Deepak, M. Mathew, Abraham T. Natl Inst Technol Calicut Dept Elect Engn Kozhikode 673601 Kerala India Mar Baselios Coll Engn & Technol Dept Elect & Elect Engn Thiruvananthapuram Kerala India

Developing an optimization algorithm with independent algorithm-specific parameters is crucial in tuning the controller parameters of Automatic Generation Control (AGC). In 2020, rao developed a robust and newly proposed algorithm independent of algorithm-specific parameters with faster convergence and less computational complexities. This paper presents the AGC of a sample two-area interconnected multi-source power systems with fractional-order PID controllers optimized using the rao algorithm. The objective function selected for tuning the optimal gain of the controller using the rao algorithm is based on Integral Squared Error (ISE). The robustness of the rao algorithm for parameter variations and load changes is compared with other metaheuristic algorithms such as Genetic algorithm (GA), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). The efficacy of the proposed tuning method for AGC application is validated using the dSPACE 1103 hardware-in-loop simulation.

关键词： automatic generation control integral squared error rao algorithm fractional order PID controller

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Optimization of Parameters in Additive Manufacturing Processes Using rao algorithms 4th

Optimization of Parameters in Additive Manufacturing Process...

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4th International Conference on Advanced Engineering Optimization Through Intelligent Techniques

作者： Pabari, Miit Chetan Patel, Pooja rao, Ravipudi Venkata Sardar Vallabhbhai Natl Inst Technol Dept Mech Engn Surat India

ISBN: (纸本)9789819796618;9789819746545;9789819746538

Additive manufacturing (AM) has revolutionized the manufacturing industry by enabling the creation of complex geometries and customized parts with unprecedented speed and precision. However, to fully unlock its potential, optimizing AM processes is imperative. This paper extensively explores the utilization of rao optimization algorithms within the domain of additive manufacturing, with the primary objective of elevating operational efficiency, mitigating production expenditures, and elevating the overall standard of manufactured products. Three case studies of additive manufacturing are considered in this paper to illustrate the practical implementation of rao algorithms, showcasing remarkable improvements in terms of material utilization, build time reduction, and structural integrity enhancement.

关键词： rao algorithm Additive manufacturing Process parameters Optimization

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Discrete Truss Optimization Using rao algorithms 6th

Discrete Truss Optimization Using Rao Algorithms

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6th International Conference on Geotechnics, Civil Engineering and Structures (CIGOS)

作者： Hoang-Anh Pham Viet-Hung Truong Thuy-Duong Tran Ha Noi Univ Civil Engn 55 GiaiPhong Hanoi Vietnam Thuy Loi Univ 175 Tay Son Hanoi Vietnam

ISBN: (纸本)9789811671609;9789811671593

rao algorithms are known as simple, parameter-free metaheuristics that have shown good performance and are quite competitive in solving engineering optimization problems. Although rao algorithms are quite new, they gain increasing attention from researchers. This paper freshly explores the applicability of rao algorithms in solving discrete truss optimization problems. Furthermore, a novel adaptive scheme is proposed to balance the global exploration and the local exploitation of these algorithms and a composite rao algorithm is established. Three benchmark truss structures are used to test the performance of the original and the new algorithms. The effect of the population size, the only required parameter, is investigated, and some remarks are drawn from the numerical results.

关键词： rao algorithm Truss structure Discrete optimization

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Linear Antenna Array synthesis using rao and Jaya algorithms

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INTERNATIONAL JOURNAL OF KNOWLEDGE-BASED AND INTELLIGENT ENGINEERING SYSTEMS 2022年第1期26卷 1-6页

作者： Vegesna, Nagavalli Yamuna, G. Kumar, T. Sudheer Annamalai Univ Chidambaram Tamil Nadu India Shri Vishnu Engn Coll Women Bhimavaram Andhra Pradesh India

Optimization algorithms are being widely applied in real-time applications. In recent times, Jaya and rao algorithms have been prominent. The performance of these algorithms will be analyzed for the objective function. The results thus obtained are more accurate and fast compared to previous algorithms. Also, Jaya and rao algorithms will be utilized for linear array antenna synthesis for the arrays that are equally spaced. Therefore it is of present interest to evaluate the performance of linear antenna array using these algorithms.

关键词： Linear Antenna Array Jaya algorithm rao algorithm optimization sidelobe level

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