TDR-Model: Tomato Disease Recognition Based on Image Dehazing and Improved MobileNetV3 Model by Zhixiang Zhang, Tong Liu, Jinyu Gao, Meng Yang, Wenjun Luo, Fanqiang Lin

“…However, in greenhouse tomato cultivation environments, many techniques neglect the foggy image caused by wet conditions, adversely affecting the performance of disease recognition models, which still remains unresolved. To alleviate adverse environmental impacts, such as fog, and enhance the precision and robustness of the model, this study introduces an improved dark channel prior (DCP) dehazing algorithm and proposes the TDR-Model based on the MobileNetV3. …”
Get full text

Optimization of TCN-BiLSTM for dissolved oxygen prediction based on improved sparrow search algorithm by Pei Shi, Mingjie Tang, Quan Wang, Xiaofei Ma

“…Finally, to address the stochastic nature of hyperparameter optimization in the TCN-BiLSTM module, we introduce an improved Sparrow Search Algorithm (ISSA). The ISSA is applied to optimize the hyperparameters of the TCN-BiLSTM model, thereby improving the overall prediction performance. …”
Get full text

Research on location algorithm of opencast mine vehicle based on improved adaptive H ∞ CKF and IAGA by Zhen Yang, Liwen Ji, Xin Li, Haoyuan Liu, Jianxiong Li, Dianxing Sun, Ruiheng Sun

“…Improved Adaptive Genetic Algorithm (IAGA) updates the optimal preservation strategy of traditional genetic algorithm and redefines the adaptive cross rate and variation rate. …”
Get full text

Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles by Naif Almakayeel

“…This manuscript proposes a Deep Learning-Based Improved Transformer Model on Android Malware Detection (DLBITM-AMD) technique for Internet vehicles (IoVs). …”
Get full text

DEVELOPMENT THE MODEL OF IMPROVING THE QUALITY OF TRAINING by A. Panychev

“…Developed the model of improving the training of specialists on the basis of accounting processes of improvement of qualification specialist and formation of its competences in extracurricular process. …”
Get full text

Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm by Zhao Li, Hao Zhang, Jinfeng Zhang, Bo Wu

“…To address this gap, this study investigates the operational characteristics of methanol dual-fuel liners and develops a mixed-integer nonlinear programming (MINLP) model aimed at minimizing operating costs. Furthermore, an improved genetic algorithm (GA) integrated with the Nonlinear Programming Branch-and-Bound (NLP-BB) method is proposed to solve the model. …”
Get full text

Improving Genetic Algorithm with Fine-Tuned Crossover and Scaled Architecture by Ajay Shrestha, Ausif Mahmood

“…Our implementation tests show that leveraging these new concepts of mtDNA and Continental Model results in relative improvement of the optimization quality of GA.…”
Get full text

Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

Subjects: Get full text

IMPROVING OF HYDROCARBON FUELS ACCOUNTING in FUEL FARMS by Y. N. Ribakov, S. I. Chirikov, R. I. Kyunnap

“…The article outlines the theoretical approaches to the assessment of technological losses of petroleum products during storage in flexible tanks with flexible account of steady and unsteady regimes fuels diffusion through structural material of tanks. The proposed algorithm and mathematical model for determining technological losses, taking into account the unsteady measurement mode structural material elastic reservoirs, can significantly (up to 40 %) improve the accuracy of the valuation of natural loss of hydrocarbon fuels at fuel depots field.…”
Get full text

Improvement and Characteristic Analysis of Car-Following Models in Mixed Traffic Flow Based on Empirical Datasets by Huanfeng Liu, Hanfei Wang, Ziyan Wu, Anning Song, Zishuo Zhang

“…First, the potential car-following patterns in mixed traffic are analyzed, and an improvement to the Intelligent Driver Model (IDM) is made by incorporating dynamic response times. …”
Get full text

Evaluation and Improvement of Generalization Performance of SAR Ship Recognition Algorithms by Chi Zhang, Xi Zhang, Jie Zhang, Gui Gao, Yongshou Dai, Genwang Liu, Yongjun Jia, Xiaochen Wang, Yi Zhang, Meng Bao

Get full text

Benchmarking and improving algorithms for attributing satellite-observed contrails to flights by A. Sarna, V. Meijer, R. Chevallier, A. Duncan, K. McConnaughay, S. Geraedts, K. McCloskey

“…In this work, we present a method for producing synthetic contrail detections with predetermined contrail-to-flight attributions that can be used to evaluate – or “benchmark” – and improve such attribution algorithms. The resulting performance metrics can be employed to understand the implications of using these observational data in downstream tasks, such as forecast model evaluation and the analysis of contrail avoidance trials, although the metrics do not directly quantify real-world performance. …”
Get full text

Improvement of reading platforms assisted by the spring framework: A recommendation technique integrating the KGMRA algorithm and BERT model by Yawen Su

“…To address these limitations, this study introduces a novel recommendation system that combines the Knowledge Graph-based Multi-Relational Association (KGMRA) algorithm with the Bidirectional Encoder Representations from Transformers (BERT) model. …”
Get full text

Optimization of stamping workshop line layout based on improved PSO algorithm by Yaxuan Bi, Xin Ning, Shuai Zhao

“…This study proposes a mathematical model and introduces an enhanced Particle Swarm Optimization (PSO) algorithm to address this challenge. …”
Get full text

Performance Analysis of Battery State Prediction Based on Improved Transformer and Time Delay Second Estimation Algorithm by Bo Gao, Xiangjun Li, Fang Guo, Xiping Wang

“…The Time Delay Second Estimation (TDSE) algorithm optimized the improved Transformer model to overcome traditional models’ limitations in extracting long-term dependency. …”
Get full text

Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments by Sarah A. Alzakari, Mohammed Aljebreen, Mashael M. Asiri, Wahida MANSOURI, Sultan Alahmari, Mohammed Alqahtani, Shaymaa Sorour, Wafi Bedewi

“…This study presents Cybersecurity using a Crested Porcupine Optimizer Algorithm with Hybrid Deep Learning Models (CCPOA-HDLM). …”
Get full text

Research on the Time-varying Meshing Stiffness Algorithm of Spur Gears Based on an Improved Potential Energy Method by Xu Kejun, Jiao Wei, Qin Haiqin

Get full text

OptiSGD-DPWGAN: Integrating Metaheuristic Algorithms and Differential Privacy to Improve Privacy-Utility Trade-Off in Generative Models by Alshaymaa Ahmed Mohamed, Yasmine N. M. Saleh, Ayman A. Abdel-Hamid

Get full text

Improve the robustness of algorithm under adversarial environment by moving target defense by Kang HE, Yuefei ZHU, Long LIU, Bin LU, Bin LIU

“…Traditional machine learning models works in peace environment,assuming that training data and test data share the same distribution.However,the hypothesis does not hold in areas like malicious document detection.The enemy attacks the classification algorithm by modifying the test samples so that the well-constructed malicious samples can escape the detection by machine learning models.To improve the security of machine learning algorithms,moving target defense (MTD) based method was proposed to enhance the robustness.Experimental results show that the proposed method could effectively resist the evasion attack to detection algorithm by dynamic transformation in the stages of algorithm model,feature selection and result output.…”
Get full text

Development and external validation of prediction algorithms to improve early diagnosis of cancer by J. Hippisley-Cox, CA Coupland

“…Abstract Cancer prediction algorithms are used in the UK to identify individuals at high probability of having a current, as yet undiagnosed cancer with the intention of improving early diagnosis and treatment. …”
Get full text