Intelligent interference decision algorithm with prior knowledge embedded LSTM-PPO model by ZHANG Jingke, YANG Kai, LI Chao, WANG Hongyan

“…Focusing on the issues of low efficiency and effectiveness in decision-making as well as the instability of traditional reinforcement learning model-based multi-function radar (MFR) jamming decision algorithms, a prior knowledge embedded long short-term memory (LSTM) network-proximal policy optimization (PPO) model based intelligent interference decision algorithm was developed. …”
Get full text

Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
Get full text

Modelling and optimization for cognitive radio networks with preemption backoff mechanism by Yuan Zhao, Zhiyu Xiang, Kang Chen, Zhisheng Ye, Qi Lu

“…At last, we design a cost function by compromising various performance indices and find the optimum parameter combination under the lowest system cost through the Transient Search Optimization (TSO) algorithm. The numerical and simulation results illustrate our proposed PBM can improve SUs’ transmission continuity. …”
Get full text

Research on E-Commerce Inventory Sales Forecasting Model Based on ARIMA and LSTM Algorithm by Chenyang Wang, Junsheng Wang

Get full text

Multi-objective DG placement in radial distribution systems using the IbI logic algorithm by Nitin Saxena, M Pandit, L Srivastava

Get full text

Detection of abnormal tourist behavior in scenic spots based on optimized Gaussian model for background modeling by Liu Xiaohua

“…The study proposed a background model constructed by an optimized Gaussian mixture model based on the background subtraction method to eliminate the background interference. …”
Get full text

Modelling and optimization of TPMLMs with slotted stators based on Bayesian DNN by Tao Wu, Peipei Dai, Kai Zhu, Yachao Zhu

Get full text

Antenna Optimization Design Based on Deep Gaussian Process Model by Xin-Yu Zhang, Yu-Bo Tian, Xie Zheng

“…When using Gaussian process (GP) machine learning as a surrogate model combined with the global optimization method for rapid optimization design of electromagnetic problems, a large number of covariance calculations are required, resulting in a calculation volume which is cube of the number of samples and low efficiency. …”
Get full text

Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm by Rafiqul Islam, Md. Arif Hossain

“…This paper introduces a novel methodology for predicting Unconfined Compressive Strength (UCS) in rocks by integrating Support Vector Regression (SVR) with two cutting-edge optimization algorithms: the Seahorse Optimizer (SO) and the COOT Optimization Algorithm (COOT). …”
Get full text

Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms by Maryam Askari, Farid Khoshalhan, Hodjat Hamidi

“…In this research, we introduce the Improved Multi-Verse Optimizer (IMVO) algorithm, a novel feature selection method that integrates the Multi-Verse Optimizer (MVO) with local search algorithms (LSAs). …”
Get full text

MULTI-OBJECTIVE OPTIMIZATION DESIGN OF ROADHEADER’S CUTTING HEAD BASED ON THE GA by ZHAO LiJuan, FAN JiaYi

“…In order to improve the dynamic reliability of the roadheader,the roadheader’s rigid-flexible coupled model was established based on virtual prototyp,dynamic reliability analysis was done on the rotary table of different structural parameters,evaluation function was established based on mechanical optimization design theory,the function’s design variables was half cone angle,helix Angle and cutting line spacing, the function’s objective function was the minimization of maximum equivalent stress as the objective function.The cutting head’s optimal structural parameters was obtained by genetic algorithm.Based on the cutting productivity and rotary table equivalent stress, the optimal yawing speed was obtained by optimized multi-objective.The results shows that after two optimizations,rotary table maximum stress is decreased 18.495 MPa,the fatigue life is improved from 3.067 E4 to 3.326 E6,productivity is improved 18.6 t/h,prediction error is less than 1.3%,meet the design requirement.This method provides data support for the structure and kinematic parameters of cutting head,provides a new method for the optimization design of heavy complicated mechanical equipment.…”
Get full text

Target image detection algorithm of complex road scene based on improved multi-scale adaptive feature fusion technology by Xu Zhaosheng, Liao Zhongming, Xiao Xiaoyong, Ahmad Suzana, Mat Diah Norizan, Ismail Azlan

Get full text

Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…Aiming at the problem of drought forecasting accuracy in a short time scale, this study proposed a drought forecasting model named VMD-JAYA-Informer based on Variational Mode Decomposition (VMD) and the JAVA optimization algorithm to improve the Informer model. …”
Get full text

Optimization of Adversarial Reprogramming for Transfer Learning on Closed Box Models by Alexander Bott, Moritz Siems, Alexander Puchta, Jurgen Fleischer

Get full text

Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease by Tiantian Bai, Mengru Xu, Taotao Zhang, Xianjie Jia, Fuzhi Wang, Xiuling Jiang, Xing Wei

“…This study focuses on integrating swarm intelligence feature selection algorithms (including whale optimization algorithm, cuckoo search algorithm, flower pollination algorithm, Harris hawk optimization algorithm, particle swarm optimization algorithm, and genetic algorithm) with machine learning technology to improve the early diagnosis of cardiovascular disease. …”
Get full text

Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…The model’s hyperparameters are optimized using the IDBO. …”
Get full text

Machine learning approach for optimizing usability of healthcare websites by Amandeep Kaur, Jaswinder Singh, Satinder Kaur

Get full text

Tackling Blind Spot Challenges in Metaheuristics Algorithms Through Exploration and Exploitation by Matej Črepinšek, Miha Ravber, Luka Mernik, Marjan Mernik

“…Furthermore, evaluations on standard benchmarks without blind spots, such as CEC’15 and the soil model problem, confirm that LTMA+ maintains strong optimization performance without introducing significant computational overhead.…”
Get full text

Direct methanol fuel cells parameter identification with enhanced algorithmic technique by Manish Kumar Singla, Muhammed Ali S.A, Ramesh Kumar, Hamed Zeinoddini-Meymand, Farhad Shahnia

“…The parameter of a direct methanol fuel cell (DMFC) can be identified using optimization techniques to determine the optimal unknown parameter values that are needed for creating an accurate fuel cell performance prediction model. …”
Get full text

An enhanced multi-objective reactive power dispatch for hybrid Wind-Solar power system using Archimedes optimization algorithm by Prisma Megantoro, Syahirah Abd Halim, Nor Azwan Mohamed Kamari, Lilik Jamilatul Awalin, Ramizi Mohamed, Hazwani Mohd Rosli

“…This paper proposes a solution to the ORPD problem in systems with RE-DG integration using the Archimedes Optimization Algorithm (AOA). The uncertainties of wind and solar power generation were modelled using Weibull and lognormal probability density functions (PDFs), respectively, and the optimization model was tested using a scenario-based method. …”
Get full text