Mathematical modelling and optimization of cutting conditions in turning operation on MDN 350 steel with carbide inserts by Syed Adil, A. Krishnaiah, D. Srinivas Rao

“…Genetic Algorithm, which is an advanced optimization technique known for its intricate search for optimal solutions, is used for optimizing surface roughness with optimal combination of the geometrical parameters. …”
Get full text

Model order reduction of boiler system using nature-inspired metaheuristic optimization of PID controller by Anurag Singh, Shekhar Yadav, Nitesh Tiwari, Dinesh Kumar Nishad, Saifullah Khalid

“…This study proposes a dual-stage optimization framework that integrates balanced truncation-based model order reduction with nature-inspired metaheuristic algorithms for PID controller tuning to address these issues. …”
Get full text

Detection of Hepatocellular Carcinoma Using Optimized miRNA Combinations and Interpretable Machine Learning Models by Zhengwu Long, Lisheng Zhang

Get full text

Research on the Prediction Model of Wheel Set Failure Rate for Urban Rail Trains Based on IPSO-BP Algorithm by HE Deqiang, SUN Yi, MENG Jiwei, LIU Jianren

Get full text

Improved YOLO for long range detection of small drones by Sicheng Zhou, Lei Yang, Huiting Liu, Chongqin Zhou, Jiacheng Liu, Yang Wang, Shuai Zhao, Keyi Wang

“…Inspired by ARM CPU efficiency optimizations, the model uses depthwise separable convolutions and efficient activation functions to reduce parameter size. …”
Get full text

SAMFA: A Flame Segmentation Algorithm for Infrared and Visible Aerial Images in the Same Scene by Jianye Yuan, Min Yang, Haofei Wang, Xinwang Ding, Song Li, Wei Gong

“…In response to the issues of poor flame segmentation performance in the current fire images and the large number of learnable parameters in large models, we propose an improved large model algorithm, SAMFA (Segmentation Anything Model, Fire, Adapter). …”
Get full text

Optimization of Backpropagation (BP) Weight Values Using Particle Swarm Optimization (PSO) to Predict KIP Scholarship Recipients by Dika Kurnia Nanda, Dian Palupi Rini

“…PSO is a simple but effective optimization algorithm to find optimal weights more quickly and accurately. …”
Get full text

Hybrid Models for Forecasting Allocative Localization Error in Wireless Sensor Networks by Guo Li, Hongyu Sheng

“…The approach utilizes Radial Basis Function (RBF) models enhanced with advanced optimization algorithms, including Coot Optimization Algorithm (COA), Smell Agent Optimization (SAO), and Northern Goshawk Optimization (NGO) to improve ALE prediction accuracy. …”
Get full text

Optimization of Teaching Management System Based on Association Rules Algorithm by Qing Niu

“…Second, use the MapReduce calculation model to partition the transaction database, then use the improved Apriori optimization algorithm for mining, and finally merge the mining results to obtain frequent itemsets. …”
Get full text

An Optimal Algorithm for Renewable Energy Generation Based on Neural Network by Weihua Zhao, Imran Khan, Shelily F. Akhtar, Mujahed Al-Dhaifallah

“…The results show that the proposed algorithm has technological applications and may greatly improve prediction accuracy.…”
Get full text

Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…The use of CBO ensures efficient convergence with minimal parameter tuning, making the model suitable for large-scale datasets compared to conventional optimizers, including Adam, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
Get full text

FOX-TSA hybrid algorithm: Advancing for superior predictive accuracy in tourism-driven multi-layer perceptron models by Sirwan A. Aula, Tarik A. Rashid

“…Nature-inspired optimization models have received a great deal of interest due to the performance of these algorithms in solving resourceful and authentic problems. …”
Get full text

Comparative analysis of lumped and semi-distributed hydrological models for an upland watershed in Ethiopia by Gebiaw T. Ayele, Bofu Yu

Get full text

Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms by Dongmei Yu, Zitao Wang, Chao Yue, Jianping Wang

Get full text

A Gradient-Based Optimization Algorithm for Optimal Control Problems With General Conformable Fractional Derivatives by Essia Ben Alaia, Slim Dhahri, Omar Naifar

Get full text

An Immune Algorithm based Reliability Optimization Method of Circuit Board by XIA Quan, REN Yi, SUN Bo, WU Zeyu

“…This method is applied to solve the reliability optimization model of typical circuit boards, and the optimization scheme of design variables is obtained.The results are compared with genetic algorithm and ant colony algorithm.It shows that the immune algorithm has the advantages of fast convergence speed and strong optimization ability.Moreover, the calculation time is reduced by about 37.2% by the collaborative optimization strategy in the case.Thus, the collaborative optimization method based on immune algorithm proposed in this paper can effectively improve the solution efficiency of circuit board reliability optimization model.…”
Get full text

The analysis of strategic management decisions and corporate competitiveness based on artificial intelligence by Yang Pu, Hao Li, Wenjia Hou, Xingchen Pan

“…To address this issue, this work proposes a hybrid optimization model combining transformer models and reinforcement learning algorithms, designed to optimize corporate strategic decision-making processes and improve competitiveness. …”
Get full text

Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
Get full text

Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

“…Field validation showed that the productivity prediction model achieved an average error of 7.06%, providing a basis for horizontal fracture engineering design and achieving cost reduction and efficiency improvement in oilfield development.…”
Get full text

Application of Adaptive Genetic Algorithm in Optimal Scheduling of Aviation Materials by Jinqiu Shang

“…This research establishes the model of air material scheduling problem and introduces NSGA-II genetic algorithm with adaptive design to optimize the air material scheduling arrangement. …”
Get full text