Adaptive multichannel detection-resolution of stochastic signals in conditions of parametric prior uncertainty by A. V. Filonovich, I. V. Vornacheva, N. A. Tuyakbasarova, A. S. Chernyshev

“…Results. In this paper, the problems of synthesis of adaptive multichannel detection-resolution algorithms for stochastic signals of various structures under the influence of intense noise interference are considered. …”
Get full text

A hybrid attack detection strategy for cybersecurity using moth elephant herding optimisation‐based stacked autoencoder by Abdullah Shawan Alotaibi

Get full text

SAR Images Change Detection Based on Attention Mechanism-Convolutional Wavelet Neural Network by Jiahui E, Lu Wang, Chunhui Zhao, P. Takis Mathiopoulos, Tomoaki Ohtsuki, Fumiyuki Adachi

“…To deal with these problems this article proposes a SAR images change detection scheme which is based upon an Attention Mechanism and Convolutional Wavelet Neural Network. …”
Get full text

Ultrasonic localization method based on Chan‐WLS algorithm for detecting power transformer partial discharge faults by fibre optic F‐P sensing array by Hong Liu, Tianhe Yang, Zhixian Zhang, Haoyuan Tian, Yuxuan Song, Qiuxia Sun, Wei Wang, Yunjun Geng, Weigen Chen

“…A system of non‐linear equations is developed by utilising the time difference of arrival (TDOA) of the partial discharge ultrasound signal propagation to the F‐P sensing array. The Chan‐WLS algorithm is used to convert the non‐linear equations in the TDOA localisation method into a non‐linear optimisation problem to be solved and experimentally verified on the 220 kV real power transformer. …”
Get full text

Sinkhole attack detection based on fusion of ACO and P2P trust model in WSN by Wumaier HENIGULI

“…For the Sinkhole attack problem of wireless sensor network（WSN），a detection algorithm based on fusion of ant colony optimization（ACO）and P2P trust model was proposed.Firstly，ant colony optimization algorithm was used to detect the existence of a Sinkhole attack in route and generate the alarm information of sensor nodes. …”
Get full text

Sinkhole attack detection based on fusion of ACO and P2P trust model in WSN by Wumaier HENIGULI

“…For the Sinkhole attack problem of wireless sensor network（WSN），a detection algorithm based on fusion of ant colony optimization（ACO）and P2P trust model was proposed.Firstly，ant colony optimization algorithm was used to detect the existence of a Sinkhole attack in route and generate the alarm information of sensor nodes. …”
Get full text

Improving heat exchanger fouling detection for phosphoric acid concentration units: A hybrid inverse approach integrating genetic algorithms and the Levenberg-Marquardt technique by Ridha Zitouni, Ali Fguiri, Amine Aymen Assadi, Mohammod Hafizur Rahman, Abdetif Amrane, Juan Pedro Solano, Mohamed-Razak Jeday

Get full text

Data-driven Detection and Identification of Line Parameters with PMU and Unsynchronized SCADA Measurements in Distribution Grids by Jinping Sun, Qifang Chen, Mingchao Xia

“…To solve this problem, a data-driven method is proposed. SCADA measurements are taken as samples and PMU measurements as the population. …”
Get full text

Target detection technology of coal mine wheeled robot combining improved CNN and self attention mechanism by Junfei TANG, Hailong XING, Su LI, Taotao ZHANG, Heng LIU, Shiyu YAO

Get full text

Internet of things driven object detection framework for consumer product monitoring using deep transfer learning and hippopotamus optimization by Amnah Alshahrani, Mukhtar Ghaleb, Hany Mahgoub, Achraf Ben Miled, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Hasan Beyari, Sultan Alanazi

“…It utilizes advanced holography to create virtual projections in real-time environments. Object detection (OD) is the most significant and challenging problem in computer vision (CV). …”
Get full text

Detecting Malware C&C Communication Traffic Using Artificial Intelligence Techniques by Mohamed Ali Kazi

“…Subsequently, a methodology is proposed for detecting banking malware C&C communication traffic, and this methodology is tested using several feature selection algorithms to determine which feature selection algorithm performs the best. …”
Get full text

A new approach combining CNN, RNN, and an improved Otsu threshold method for detecting hand gestures in people with thumb finger size problems and hand tremors by Malik Kareem Kadhim, Chen Soong Der, Chen Chai Phing

Get full text

Optimizing Heart-Kidney Interaction for Cancer Detection Through Physiological Process Simulation as a Decision Support System by Najmeh Sadat Jaddi, Salwani Abdullah, Zalinda Othman, Yazrina Yahya, Mohd Zakree Ahmad Nazri, Say Leng Goh, Fatemeh Alvankarian, Jafar Alvankarian

“…Finally, the HK algorithm is applied to cancer detection from microRNA data, demonstrating its potential in optimizing decision-making processes in healthcare.…”
Get full text

Investigation of criminal offences against property: typical investigative situations and problems of applying specialised knowledge by R. L. Stepaniuk, V. O. Husieva

Get full text

A synergic quantum particle swarm optimisation for constrained combinatorial test generation by Xu Guo, Xiaoyu Song, Jian‐tao Zhou

“…Abstract Combinatorial testing (CT) can efficiently detect failures caused by interactions of parameters of software under test. …”
Get full text

Experimental study on solution possibilities of multiextremal optimization problems through heuristic methods by Rudolf A. Neydorf, Ivan V. Chernogorov, Orkhan Takhir Yarakhmedov, Victor V. Polyakh

“…It is proved that all these methods are well suited for the multiextremal problem solution. While it is necessary to use proper specific approaches to solving the local extremum detection and identification problem in each of the heuristic algorithms, they all require data clustering. …”
Get full text

Optimization Algorithm of Neural Network Structure Based on Adaptive Genetic Algorithm by XILiang, WANGRui dong

“…The structural design of neural network is one of the hot issues in neural network research The number of hidden layers and nodes has a great influence on the convergence speed and generalization ability of neural network Genetic algorithm is an adaptive optimization probability search algorithm formed by simulating biological heredity and evolution Its core idea is derived from the natural law of biological genetics and survival of the fittest, and it is a search algorithm with the iterative process of “survival + detection” However, the selection of genetic algorithm parameters is subjective, slow convergence and easy to fall into premature convergence To solve these problems, an adaptive genetic algorithm is proposed to find the optimal neural network structure The adaptive genetic algorithm selects the first n optimal individuals and adds a certain amount of random individuals in the optimization process of each iteration to update the population, and selfadaptive optimization of the search step size of the population can ensure the diversity of the population and improve the convergence rate at the same time Then we code and the structure of neural network processing, adaptive genetic algorithm, neural network structure optimization, so as to make the neural network as soon as possible to find the optimal network structure and parameters, in order to improve the accuracy of neural network. …”
Get full text

Research on the Optimization of TP2 Copper Tube Drawing Process Parameters Based on Particle Swarm Algorithm and Radial Basis Neural Network by Fengli Yue, Zhuo Sha, Hongyun Sun, Dayong Chen, Jinsong Liu

“…To address the problem of the large number of finite element model meshes and low solution efficiency, the wall thickness uniformity was predicted using a radial basis function (RBF) neural network, and parameter optimization was performed using the particle swarm optimization (PSO) algorithm. …”
Get full text

A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity by Xue-Yang Pei, Yuan Hou, Hai-Bin Huang, Jun-Xing Zheng

“…To address this challenge, this study proposes a multi-objective sensor placement optimization method based on the Non-Dominated Sorting Genetic Algorithm. The method introduces two key objective functions: minimizing modal identification uncertainty by leveraging Bayesian modal identification theory and information entropy and maximizing damage detection sensitivity by incorporating an entropy-based measure to quantify the uncertainty in stiffness variation estimation. …”
Get full text

Beyond the Grid: GLRT-Based TomoSAR Fast Detection for Retrieving Height and Thermal Dilation by Nabil Haddad, Karima Hadj-Rabah, Alessandra Budillon, Gilda Schirinzi

Get full text