Mapping fruit tree dynamics using phenological metrics from optimal Sentinel-2 data and Deep Neural Network by Yingisani Chabalala, Elhadi Adam, Mahlatse Kganyago

“…The models were optimized to determine the best hyperparameters to achieve the best classification results. …”
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Integrated OVMD-BiGRU-SMAC Framework for Forecasting Construction Accidents in the Kingdom of Saudi Arabia by Badr T. Alsulami, Afaq Khattak

“…Construction Accidents (CA) remain a major concern for occupational safety, especially within high-risk environments such as those found across the expanding construction sector in the Kingdom of Saudi Arabia (KSA). This research introduces an innovative prediction framework that combines signal decomposition with advanced deep learning methods to estimate CA trends. …”
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Novel hybrid integrated Pix2Pix and WGAN model with Gradient Penalty for binary images denoising by Luca Tirel, Ali Mohamed Ali, Hashim A. Hashim

“…Drawing on previous work on image-to-image translation and GAN stabilization techniques, the proposed research highlights the potential of GANs as a general-purpose solution for denoising. …”
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A novel attention based vision transformer optimized with hybrid optimization algorithm for turmeric leaf disease detection by R. Selvaraj, M. S. Geetha Devasena

“…The objective of this research is overcome these limitations through a novel leaf disease detection model which incorporates Vision Transformer (ViT) with hybrid Falcon-Bowerbird Optimization (FBO). …”
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IoT-Based Traffic Prediction for Smart Cities by Zhinong Miao, Qilong Liao

“…The study suggests that integrating advanced machine learning techniques like CNNs and PSO can lead to more efficient and adaptive traffic management solutions, contributing to the development of smarter, more resilient urban environments. Future research could expand on these findings by incorporating additional data sources and testing the model’s scalability and real-world applicability.…”
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Gas pipeline leakage detection based on multiple multimodal deep feature selections and optimized deep forest classifier by Eddie Zhang, Evan Zhang

“…Using the simulated testing dataset created for this research, our architecture demonstrated superior accuracy (98.9%) and deployability with its lower model size (115 MB). …”
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Retinal fundus imaging-based diabetic retinopathy classification using transfer learning and fennec fox optimization by Indresh Kumar Gupta, Shruti Patil, Supriya Mahadevkar, Ketan Kotecha, Awanish Kumar Mishra, Joel J.P.C. Rodrigues

“…Fennec Fox Optimization (FFO) fine-tunes the GRU hyperparameters, boosting classification accuracy, with its effectiveness demonstrated on benchmark datasets. 3. …”
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Study on Satisfaction Evaluation of Ecotourism Through Advanced Network Text Mining by Jia Gao, Leong Mow Gooi, Kim Mee Chong, Xiang Lyu, Jin Zhang

“…The LSTM model was further optimized using GA to improve its performance by fine-tuning hyperparameters such as learning rate and network depth. …”
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Temperature rise of high-speed bearing in gearbox of 5 MW wind turbine based on Bayesian-LightGBM and improved PSO-SVM troubleshooting by Minan Tang, Zhanglong Tao, Jiandong Qiu, Jinping Li, Mingyu Wang, Hongjie Wang, Chuntao Rao

“…In this paper, a combined modelling wind turbine gearbox high-speed bearing temperature rise prediction method based on Bayesian-LightGBM and improved PSO-SVM is proposed with a 5 MW wind turbine as the research object. Firstly, the initial dimensionality reduction of SCADA data is performed by sparse random projection matrix, which reduces the redundant data. …”
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Leveraging hybrid model for accurate sentiment analysis of Twitter data by Naga Surekha Jonnala, A. V. S. Ram Teja, S. Raja Rajeswari, Shaik Jakeer, Allamsetty Dheeraj, Shonak Bansal, Krishna Prakash, Shashank Singh, Mohammad Rashed Iqbal Faruque, K. S. Al-mugren

“…The extracted features are then input into a Logistic Regression model with optimized hyperparameters to classify sentiments as positive or negative. …”
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Evaluation of Coalbed Methane Content by Using Kernel Extreme Learning Machine and Geophysical Logging Data by Jianhong Guo, Zhansong Zhang, Guangshan Guo, Hang Xiao, Linqi Zhu, Chaomo Zhang, Xiao Tang, Xueqing Zhou, Yanan Zhang, Can Wang

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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

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CCT: A Cyclic Co-Teaching Approach to Train Deep Neural Networks With Noisy Labels by Jorge K. S. Kamassury, Henrique Pickler, Filipe R. Cordeiro, Danilo Silva

“…The detrimental impact of noisy labels on the generalization performance of deep neural networks has sparked research interest in learning with noisy labels (LNL). …”
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An optimized spatial target trajectory prediction model for multi-sensor data fusion in air traffic management by Jian Dong, Yuan Xu, Rigeng Wu, Chengwang Xiao

“…Consequently, there is increasing research interest in multi-sensor data fusion. This paper proposes an innovative network model based on the improved snow ablation optimizer algorithm. …”
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Joint Iterative Satellite Pose Estimation and Particle Swarm Optimization by Patcharin Kamsing, Chunxiang Cao, You Zhao, Wuttichai Boonpook, Lalida Tantiparimongkol, Pisit Boonsrimuang

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Using a Bodily Weight-Fat Scale for Cuffless Blood Pressure Measurement Based on the Edge Computing System by Shing-Hong Liu, Bo-Yan Wu, Xin Zhu, Chiun-Li Chin

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Deep attention model for arrhythmia signal classification based on multi-objective crayfish optimization algorithmic variational mode decomposition by Yihang Zhang, Hang Zhao

“…Many deep learning techniques are utilized for arrhythmia classification in current research but only based on ECG data, lacking the mathematical foundations of cardiac electrophysiology. …”
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SeqConv-Net: A Deep Learning Segmentation Framework for Airborne LiDAR Point Clouds Based on Spatially Ordered Sequences by Bin Guo, Chunjing Yao, Hongchao Ma, Jie Wang, Junhao Xu

“…Therefore, the task of semantic segmentation of point clouds has been widely applied in fields such as robotics and autonomous driving. Although existing research has made unprecedented progress, achieving real-time semantic segmentation of point clouds on airborne devices still faces challenges due to excessive computational and memory requirements. …”
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A comparative study of machine learning models for automated detection and classification of retinal diseases in Ghana. by Gifty Duah, Eric Nyarko, Anani Lotsi

“…We also used the Gaussian Process-based Bayesian Optimization (GPBBO) approach to fine-tune the hyperparameters. Model performance was evaluated using the F1-Score, precision, recall, and area under the curve (AUC).…”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

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