Precise Assimilation Prediction of Short-Term and Long-Term Maize Irrigation Water Based on EnKF-DSSAT and Fuzzy Optimization-DSSAT Models by Yanshu Yu, Youxi Luo, Xinhang Wang, Xinran Wang, Chaozhu Hu

“…We also introduce a Boltzmann machine-based fusion algorithm to improve the model convergence speed and prediction accuracy. …”
Get full text

Bacterial Colony Optimization by Ben Niu, Hong Wang

“…Two types of interactive communication schemas: individuals exchange schema and group exchange schema are designed to improve the optimization efficiency. In the simulation studies, a set of 12 benchmark functions belonging to three classes (unimodal, multimodal, and rotated problems) are performed, and the performances of the proposed algorithms are compared with five recent evolutionary algorithms to demonstrate the superiority of BCO.…”
Get full text

Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…First, the sparrow search algorithm is used to optimize the hyperparameters of the RBFNN. …”
Get full text

Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…This work points out the possibility of taking complete advantage of advanced machine learning algorithms along with metaheuristics optimization in improving photocatalytic processes, hence opening a bright avenue for real applications in water treatment.…”
Get full text

Integrative Path Planning for Multi-Rotor Logistics UAVs Considering UAV Dynamics, Energy Efficiency, and Obstacle Avoidance by Kunpeng Wu, Juncong Lan, Shaofeng Lu, Chaoxian Wu, Bingjian Liu, Zenghao Lu

Get full text

Bearing Fault Diagnosis based on ACSBP Algorithm by Cheng Jiatang, Xiong Yan

“…The diagnostic results show that the ACSBP algorithm has stronger fault tolerance compared with CSBP and PSOBP models,and can effectively improve the accuracy of bearing fault diagnosis.…”
Get full text

An efficient patient’s response predicting system using multi-scale dilated ensemble network framework with optimization strategy by Nalini Manogaran, Nirupama Panabakam, Durai Selvaraj, Koteeswaran Seerangan, Firoz Khan, Shitharth Selvarajan

“…The Repeated Exploration and Exploitation-based Coati Optimization Algorithm (REE-COA) is employed to select the features. …”
Get full text

QPSO-Based Adaptive DNA Computing Algorithm by Mehmet Karakose, Ugur Cigdem

“…In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). …”
Get full text

Comparison of clustering methods and conventional approaches for geological fracture analysis: A case study in northern Shiraz, Iran by HAJAR KAZEMI, KOUROS YAZDJERDI, ABDOLMAJID ASADI, MOHAMMAD REZA MOZAFARI

Get full text

Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics by Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea, Cristian Constantin Volovăț

“…These results demonstrate that hybrid models combining deep learning and traditional ML techniques can improve predictive accuracy. …”
Get full text

Deep Reinforcement Learning-Based Distribution Network Planning Method Considering Renewable Energy by Liang Ma, Chenyi Si, Ke Wang, Jinshan Luo, Shigong Jiang, Yi Song

“…Based on the proximal policy optimization algorithm, an actor-critic-based autonomous generation and adaptive adjustment model for DNP is constructed. …”
Get full text

Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…Three key innovations drive this research: (1) A dynamic PSO algorithm incorporating adaptive learning factors and nonlinear inertia weight for precise RBF parameter optimization; (2) A hierarchical feature processing strategy combining mutual information selection with correlation-based dimensionality reduction; (3) Adaptive model architecture adjustment for small-sample scenarios. …”
Get full text

Neural network-based link prediction algorithm by Yonghao PAN, Hongtao YU, Shuxin LIU

“…To improve the difference existed in the link prediction accuracy and adaptability of different topology structure similarity based methods,a neural network-based link prediction algorithm,which fused similarity indices by neural network was proposed.The algorithm uses neural network to study the numerical characteristics of different similarity indices,and uses particle swarm optimization to optimize the neural network,and calculates the fusion index by the optimized neural network model.The experiment on the real network data set shows that the prediction accuracy of the algorithm is obviously higher than that before the fusion,and the accuracy is better than the existing methods.…”
Get full text

Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

“…This study introduces a hybrid AI-based optimization framework to enhance climbing perch aquaculture in smart farming systems, targeting improvements in both productivity and cost-efficiency. …”
Get full text

Enhancing SAR-ATR Systems’ Resistance to S2M Attacks via FUA: Optimizing Surrogate Models for Adversarial Example Transferability by Xiaying Jin, Shuangju Zhou, Chenyu Wang, Mingxin Fu, Quan Pan, Yang Li

“…Finally, Architecture modification phase modifies the activation functions and skip connections of the model architecture with the parameters fixed. Experimental results demonstrate that FUA can outperform SOTA methods and significantly improve the S2M transferability across various adversarial attack algorithms. …”
Get full text

Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…This study presents a novel hybrid modeling framework that combines Response Surface Methodology (RSM) with machine learning (ML) algorithms– Support Vector Regression (SVR) and Gradient Boosting Regression (GBR)– to contribute to the predictive modeling and optimization of thermally-activated ZnFe-LDH based Fenton catalysis. …”
Get full text

Steganographic model to conceal the secret data in audio files utilizing a fourfold paradigm: Interpolation, multi-layering, optimized sample space, and smoothing by Daffa Tristan Firdaus, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Didacienne Mukanyiligira, Louis Sibomana

“…To address these limitations, this study offers valuable insights to guide researchers in developing high-performing audio steganography models. The proposed method seeks to improve stego audio quality by implementing a smoothing-based technique and optimizing the sample space through linear interpolation, followed by a multi-layering process. …”
Get full text

The Application of Artificial Intelligent Algorithms in Electric Propulsion by Tian Bin, An Bingchen, Xie Kan, Yang Sulan

“…These algorithms can not only train models based on data to optimize the performance of electric thrusters, but also analyze and solve the mathematical and physical models of plasmas within electric thrusters. …”
Get full text

Capacity Prognostics of Marine Lithium-Ion Batteries Based on ICPO-Bi-LSTM Under Dynamic Operating Conditions by Qijia Song, Xiangguo Yang, Telu Tang, Yifan Liu, Yuelin Chen, Lin Liu

“…First, the battery is simulated according to the actual operating conditions of an all-electric ferry, and in each charge/discharge cycle, the sum, mean, and standard deviation of each parameter (current, voltage, energy, and power) during battery charging, as well as the voltage difference before and after the simulated operating conditions, are calculated to extract a series of features that capture the complex nonlinear degradation tendency of the battery, and then a correlation analysis is performed on the extracted features to select the optimal feature set. Next, to address the challenge of determining the neural network’s hyperparameters, an improved crested porcupine optimization algorithm is proposed to identify the optimal hyperparameters for the model. …”
Get full text

CRIMINALISTIC CHARACTERISTICS OF CRIMES RELATED TO ILLEGAL ACCESS TO COMPUTER INFORMATION by KHARISOVA Zarina Irekovna

Get full text