High-Performance Identification and Control of MIMO (Multiple Input—Multiple Output) Experimental Module with Fractional-Order Approach Application by Alexandre Marques de Almeida, Alisson Luan Daga, Rafael Palma Setti Penteado Lanzarini, Ervin Kaminski Lenzi, Marcelo Kaminski Lenzi

“…An important aspect concerns the use of Particle Swarm Optimization (PSO) metaheuristic algorithm for optimization tasks, both in parameter estimation and controller tuning. …”
Get full text

From Land Conservation to Famers’ Income Growth: How Advanced Livelihoods Moderate the Income-Increasing Effect of Land Resources in an Ecological Function Area by Xinyu Zhang, Yiqi Zhang, Yanjing Yang, Wenduo Wang, Xueting Zeng

Get full text

AutoML: A systematic review on automated machine learning with neural architecture search by Imrus Salehin, Md. Shamiul Islam, Pritom Saha, S.M. Noman, Azra Tuni, Md. Mehedi Hasan, Md. Abu Baten

“…AutoML emerged to increase productivity and efficiency by automating as much as possible the inefficient work that occurs while repeating this process whenever machine learning is applied. …”
Get full text

The Hydrodynamic Performance of a Vertical-Axis Hydro Turbine with an Airfoil Designed Based on the Outline of a Sailfish by Aiping Wu, Shiming Wang, Chenglin Ding

“…Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. …”
Get full text

An Innovative Smart Irrigation Using Embedded and Regression-Based Machine Learning Technologies for Improving Water Security and Sustainability by Abdennabi Morchid, Abdennacer Elbasri, Zahra Oughannou, Hassan Qjidaa, Rachid El Alami, Badre Bossoufi, Saleh Mobayen, Pawel Skruch

“…This study proposes an irrigation system based on embedded systems, using sensors and algorithms to collect and analyze data in order to optimize water management. …”
Get full text

A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
Get full text

Expedited re-design of multi-band passive microwave circuits using orthogonal scaling directions and gradient-based tuning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

“…In particular, the employment of a given passive structure in a different application area often requires re-adjustment of the operating frequencies/bands while maintaining top performance. Achieving this necessitates the utilization of numerical optimization methods. …”
Get full text

Dual-target WOA spectrum sharing algorithm based on Stackelberg game by Li ZHANG, Tian LIAO, Yejun HE

“…In order to solve the complex spectrum allocation problem,a dual-target whale optimization algorithm (WOA) with strong parallel computing capabilities was introduced,and a Stackelberg game model was proposed that could effectively reflect the actual spectrum requirements,and a dual-target WOA optimized distributed antenna system (DAS) spectrum sharing scheduling algorithm was designed.Simulation results show that performance comparison is performed from multiple indicators such as optimal pricing and user benefits.The proposed algorithm has a good spectrum sharing allocation effect,can achieve fair and effective spectrum allocation,and provides an important reference for the future communication network spectrum sharing mode.…”
Get full text

Techno-economic analysis and energy management strategies for micro gas turbines: A state-of-the-art review by A.H. Samitha Weerakoon, Mohsen Assadi

“…Additionally, the optimization of Micro Gas Turbine systems using advanced algorithms enhances energy efficiency by 10–15%, highlighting the importance of smart control systems and optimal component sizing. …”
Get full text

Sparse support path generation for multi-axis curved layer fused filament fabrication by Tak Yu Lau, Dong He, Yamin Li, Yihe Wang, Danjie Bi, Lulu Huang, Pengcheng Hu, Kai Tang

“…Firstly, the overhang regions are detected by identifying the overhang points given a multi-axis nozzle path. Then, an optimization framework for the support guide curve is proposed to minimize its total length while ensuring that overhang filaments can be stably supported. …”
Get full text

A trade-off between line hardening and dynamic line rating by a new convex optimization model for resilient micro-grid-oriented expansion planning of reconfigurable smart distribut... by Saeed Behzadi, Amir Bagheri

“…The simulation results demonstrate the efficacy of the conducted model. According to the optimal Pareto algorithm solution, the resiliency index is guaranteed to be more than 92% in the face of LPHI disasters. …”
Get full text

Evolutionary search algorithm for learning activation function of an artificial neural network by Yurshin Viacheslav

“…The proposed method aims to enhance the efficiency of the search process for optimal activation functions. Our algorithm employs genetic programming to evolve the general form of activation functions, while gradient descent optimizes their parameters during network training. …”
Get full text

Use of schedule theory algorithms for task planning and time management tasks by М. Шматко, О. Жураковська

“…At the moment, there are many algorithms for solving such tasks, but the algorithms must be customized to specific conditions, while ensuring the quality of the task and performance. …”
Get full text

Co‐Creation in Automated Public Space Lighting Design: Enhancing Safety and Reducing Light Pollution by Jan Cudzik, Michał Nessel, Victor Moczarski

“…The article presents an algorithm that iteratively determines the optimal number and placement of lamps based on expected lighting levels. …”
Get full text

Image forgery detection algorithm based on U-shaped detection network by Zhuzhu WANG

“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
Get full text

Image forgery detection algorithm based on U-shaped detection network by Zhuzhu WANG

“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
Get full text

Packet-loss robust scalable authentication algorithm for compressed image streaming by Xiao-wei YI, Heng-tai MA, Gang ZHENG, Chang-wen ZHENG

“…To construct the authentication algorithm by hash chaining and error-correction coding, the proposed approach can realize optimizing bit-rate allocations and unequal authentication protection. …”
Get full text

BeSnake: A Routing Algorithm for Scalable Spin-Qubit Architectures by Nikiforos Paraskevopoulos, Carmen G. Almudever, Sebastian Feld

“…It also has the option to adjust the level of optimization and to dynamically tackle parallelized routing tasks, all the while maintaining noise awareness. …”
Get full text

Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

Get full text

Image Similarity Quantum Algorithm and Its Application in Image Retrieval Systems by Qingchuan Yang, Xianing Feng, Lianfu Wei

“…It is found that the AE-QIP algorithm achieves comparable precision to the ST-QIP algorithm while exhibiting significant reductions in qubit consumption and average processing time. …”
Get full text