YOLOv8 forestry pest recognition based on improved re-parametric convolution by Lina Zhang, Shengpeng Yu, Bo Yang, Shuai Zhao, Ziyi Huang, Zhiyin Yang, Helong Yu

“…The model achieved a Map@0.5:0.95(%) of 88.6%, representing a 4.2% improvement over the original YOLOv8 model. …”
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Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning by Wajahat Hussain, Muhammad Faheem Mushtaq, Mobeen Shahroz, Urooj Akram, Ehab Seif Ghith, Mehdi Tlija, Tai-hoon Kim, Imran Ashraf

“…The GA optimizes the number of layers, kernel size, learning rates, dropout rates, and batch sizes of the CNN model to improve the accuracy and performance of the model. …”
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Optimization of a photovoltaic/wind/battery energy-based microgrid in distribution network using machine learning and fuzzy multi-objective improved Kepler optimizer algorithms by Fude Duan, Mahdiyeh Eslami, Mohammad Khajehzadeh, Ali Basem, Dheyaa J. Jasim, Sivaprakasam Palani

“…The variables are microgrid optimal location and capacity of the HMG components in the network which are determined through a multi-objective improved Kepler optimization algorithm (MOIKOA) modeled by Kepler’s laws of planetary motion, piecewise linear chaotic map and using the FDMT. …”
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Optimization Models for Reducing the Air Pollutants Emission in the Production of Insulation Bituminous by Faezeh Borhani, Majid Shafiepour Motlagh, Amir Houshang Ehsani, Yousef Rashidi, Alireza Noorpoor, Saeid Maddah

“…For this purpose, first, the flow parameters of the chimney are measured with the KIMO gas analyzer, model KIGAS300, and then the pollutants Carbon monoxide, Hydrocarbons, and Nitrogen oxides are optimized of two methods in the MATLAB software using the Genetic Algorithm method and python software using the multiple regression with Sklearn and Statsmodels approach. …”
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Multi-step Prediction of Monthly Sediment Concentration Based on WPT-ARO-DBN/WPT-EPO-DBN Model by GAO Xuemei, CUI Dongwen

“…Accurate multi-step sediment concentration prediction is of significance for regional soil erosion control,flood control and disaster reduction.To improve the multi-step prediction accuracy of sediment concentration and the prediction performance of the deep belief network (DBN),this paper proposes a multi-step prediction model of monthly sediment concentration by combining the artificial rabbit optimization (ARO) algorithm,eagle habitat optimization (EPO) algorithm,and DBN based on wavelet packet transform (WPT).The model is validated using time series data of monthly sediment concentration from Longtan Station in Yunnan Province.Firstly,WPT is employed to decompose the time series data of the monthly sediment concentration of the case in three layers,and eight more regular subsequence components are obtained.Secondly,the principles of ARO and EPO algorithms are introduced,and hyperparameters such as the neuron number in the hidden layer of DBN are optimized by ARO and EPO.Meanwhile,WPT-ARO-DBN and WPT-EPO-DBN prediction models are built,and WPT-PSO (particle swarm optimization)-DBN and WPT-DBN are constructed for comparative analysis.Finally,four models are adopted to predict each subsequence component,and the predicted values are superimposed to obtain the multi-step prediction results of the final monthly sediment concentration.The results are as follows.① WPT-ARO-DBN and WPT-EPO-DBN models have satisfactory prediction effects on the monthly sediment concentration of the case from one step ahead to four steps ahead.This yields sound prediction results for five steps ahead.The prediction effect for six steps ahead and seven steps ahead is average,and the prediction accuracy for eight steps ahead is poor and cannot meet the prediction accuracy requirements.② The multi-step prediction performance of WPT-ARO-DBN and WPT-EPO-DBN models is superior to WPT-PSO-DBN models and far superior to WPT-DBN models,with higher prediction accuracy,better generalization ability,and larger prediction step size.③ ARO and EPO can effectively optimize DBN hyperparameters,improve DBN prediction performance,and have better optimization effects than PSO.Additionally,WPT-ARO-DBN and WPT-EPO-DBN models can give full play to the advantages of WPT,new swarm intelligence algorithms and the DBN network and improve the multi-step prediction accuracy of monthly sediment concentration,and the prediction accuracy decreases with the increasing prediction steps.…”
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A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks by B Nagarajan, Santhosh Kumar SVN, M Selvi, K Thangaramya

“…In the course of this effort, an effective strategy for sensor node failure detection algorithm using the Poisson Hidden Markov Model (PHMM) and the Fuzzy-based Chicken Swarm Optimization (F-CSO) is proposed for efficient detection of sensor node faults in the WSN. …”
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Research on Defect Detection of Bare Film in Landfills Based on a Temperature Spectrum Model by Feixiang Jia, Yayu Chen, Wei Hao

“…Further enhancement of the edges was carried out using the guided image-filtering (GIF) algorithm, which was improved by using the edge-aware weighting in weighted guided image filtering (WGIF) and the weighted aggregation mechanism in weighted aggregated guided image filtering (WAGIF). …”
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Evaluating energy efficiency in Turkish electric distribution using network DEA and GA models by Serpil Aydin, Talat Şenel

“…For 2015, only Boğaziçi EDC is efficient among the twenty-one distribution companies evaluated in detail. The NDEA model with sub-processes provided more realistic efficiency scores than traditional DEA. …”
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Simulation Study of New Buckling Restraint Bracing Based on Bayesian Optimization Algorithm to Identify the Parameters of Modified Bouc–Wen Model by Lu Zhao, Tiangang Tu, Sunwei Ding, Xinqiao Liu

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A Smooth Jump Point Search Algorithm for Mobile Robots Path Planning Based on a Two-Dimensional Grid Model by Zhen Yang, Junli Li, Liwei Yang, Hejiang Chen

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Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling by WANG Zixuan, OU Bin, CHEN Dehui, YANG Shiyong, ZHAO Dingzhu, FU Shuyan

“…【Method】The model uses sample entropy reconstruction and the K-means clustering algorithm to optimize the adaptive noise complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) process, generating multiple intrinsic mode functions (IMF). …”
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Squirrel search algorithm-support vector machine: Assessing civil engineering budgeting course using an SSA-optimized SVM model by He Yanqing, Shi Ling, Yao Xiaoqin, Zhang Haojie, Al-Barakati Abdullah A.

“…The above results reveal that the proposed optimization algorithm and course evaluation model have good performance. …”
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Developing an Optimized Energy-Efficient Sustainable Building Design Model in an Arid and Semi-Arid Region: A Genetic Algorithm Approach by Ahmad Walid Ayoobi, Mehmet Inceoğlu

“…A comprehensive analysis and optimization model was developed using genetic algorithms to individually optimize various sustainable strategies. …”
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Analyzing social psychological impact on emotional expression through peer communication using crayfish optimization algorithm with deep learning model by Umkalthoom Alzubaidi

“…Finally, the crayfish optimization algorithm (COA) adjusts the VAE model’s hyperparameter values, improving classification. …”
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DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS by Harna M. Bodele, G. M. Asutkar, Kiran G. Asutkar

“…To overcome these issues, this text proposes design of a Dual Genetic Algorithm (DGA) based Auto regression model for Correlative prediction (AC) of Air Quality Metrics. …”
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Research on sea surface NB-IoT coverage based on improved SPM by Zheng HU, Baodan CHEN, Jia REN, Yupei FAN, Lian WANG

“…Based on the standard SPM,an improved sea surface propagation model was proposed.At the same time,a propagation model correction algorithm based on WLS algorithm was proposed.Using the CW test data of Qiongzhou Strait,the parameters of the improved SPM were corrected.Based on the corrected propagation model,the current base station of Qiongzhou Strait coast was used to carry out link level simulation and coverage simulation for NB-IoT.The experimental results show that the proposed method can effectively achieve the coverage of NB-IoT in Qiongzhou Strait and contribute to the scientific research of Internet of things.…”
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An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system by Ivan V. Stepanyan, Safa A. Hameed

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Artificial intelligence-driven cybersecurity: enhancing malicious domain detection using attention-based deep learning model with optimization algorithms by Fatimah Alhayan, Asma Alshuhail, Ahmed Omer Ahmed Ismail, Othman Alrusaini, Sultan Alahmari, Abdulsamad Ebrahim Yahya, Monir Abdullah, Samah Al Zanin

“…This manuscript presents an Enhance Malicious Domain Detection Using an Attention-Based Deep Learning Model with Optimization Algorithms (EMDD-ADLMOA) technique. …”
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Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study by Chuang Li, Youbei Lin, Xuyang Xiao, Xinru Guo, Jinrui Fei, Yanyan Lu, Junling Zhao, Lan Zhang

“…This study demonstrates that machine learning models—particularly the RF algorithm—hold substantial promise for predicting kinesiophobia in postoperative lung cancer patients. …”
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Ways to improve the efficiency of automatic control systems of pressing current collectors for railway service of high speeds by A. S. GOLUBKOV, O. A. SIDOROV, S. N. SMERDIN

“…For the considered current collector model, the optimal values of the controller coefficients are kp = 1.5 and ki= 1.0. …”
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