Bayesian-Optimized Multi-Task Gaussian Process Regression With Composite Kernels for Soybean Oil Futures Forecasting by Hui-Dong Yin, Yi-Yang Li

“…Traditional econometric models and machine learning approaches often struggle with non-stationary data and uncertainty quantification, while existing Gaussian process applications in agricultural markets remain underexplored. …”
Get full text

Python-based deep learning for optimizing thermal performance of Prandtl-Eyring hybrid nanofluids in solar systems by Nidhal Ben Khedher, Bouthaina Dammak, Zahoor Shah, Hamza Iqbal, Maryam Jawaid, Hafedh Mahmoud Zayani, Mohamed Medani

“…This study presents a Python-based hybrid framework integrating the machine learning deep learning neural network (DLNN) model and a boundary value problem solver to examine and determine the thermal behavior for Prandtl-Eyring hybrid nanofluids in conditions of solar heating. …”
Get full text

Hybrid convolutional neural network optimized with an artificial algae algorithm for glaucoma screening using fundus images by M. Shanmuga Eswari, S. Balamurali, Lakshmana Kumar Ramasamy

“…Objective We developed an optimized decision support system for retinal fundus image-based glaucoma screening. …”
Get full text

Synergistic research on planter performance optimization and green low-carbon agricultural transformation under climate risk by Yan Shi, Pengfei Zhao, Zhengzhao Gu, Ye Li

“…While traditional planting strategies focused on parameters like seed depth, speed, and spacing, they often neglected environmental sustainability and adaptability to climate variability.MethodsTo bridge this gap, we introduced the Adaptive Precision Planter Optimization Model (APPOM), which leveraged real-time environmental sensing, machine learning, and multi-objective optimization to dynamically adjust key planting parameters. …”
Get full text

A Combined Capacity Planning and Simulation Approach for the Optimization of AGV Systems in Complex Production Logistics Environments by Péter Kováts, Róbert Skapinyecz

“…Extensive series of simulation experiments are applied in the case of each model variant for optimal results and to account for machine failures in the system. …”
Get full text

Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components by Anna Konovalenko, Lars Magnus Hvattum

“…<i>Background:</i> The dynamic vehicle routing problem (DVRP) is a complex optimization problem that is crucial for applications such as last-mile delivery. …”
Get full text

Multi class aerial image classification in UAV networks employing Snake Optimization Algorithm with Deep Learning by Alanoud Al Mazroa, Nuha Alruwais, Muhammad Kashif Saeed, Kamal M. Othman, Randa Allafi, Ahmed S. Salama

“…Deep Learning (DL), a powerful tool in artificial intelligence (AI), proves significant in this context, enabling the model to analyze and classify complex aerial images effectually. …”
Get full text

Hybrid Methods Random Forest and FOX-Inspired Optimization Algorithm for Selecting Features in Cervical Cancer Data by Afidatul Masbakhah, Umu Sa'adah, Mohamad Muslikh

“…Therefore, the hybrid RF-FOX method allows the performance of the model to be more optimized, thus helping in the identification of patients at risk of cervical cancer more precisely.…”
Get full text

Red Fox Optimization-Based Estimation Algorithms for Splitting Tensile Strength of Basalt Fiber Reinforced Concrete by Xiao Wu, Daoyong Zhu, Qin Yan

“…This simulation is very dependent on its hyperparameters; to find the optimal set of hyperparameters, the red fox optimization (RFO) is linked to both LSSVR and RF. …”
Get full text

Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles by Steven M. E. Demers, Christopher Sobecki, Larry Deschaine

“…However, the expansion and testing of this model for nanoparticles of different metal composition is needed to develop a greater variety of nanosensors for medical and commercial applications. …”
Get full text

Optimized Identity Authentication via Channel State Information for Two-Factor User Verification in Information Systems by Chuangeng Tian, Fanjia Li, Xiaomeng Liu, Juanjuan Li

“…For classification, a kernel support vector machine (SVM) model is trained using a randomized hyperparameter search algorithm. …”
Get full text

Optimizing Artificial Neural Network Learning Using Improved Reinforcement Learning in Artificial Bee Colony Algorithm by Taninnuch Lamjiak, Booncharoen Sirinaovakul, Siriwan Kornthongnimit, Jumpol Polvichai, Aysha Sohail

“…Although SGD and Adam achieved faster execution times with TensorFlow, the study suggests that using PSO and improved R-ABC can improve model accuracy and efficiency. Advanced SI methods enhance the optimization process and increase the ability of ANNs to obtain optimal solutions. …”
Get full text

A Flexible Model Compression and Resource Allocation Scheme for Federated Learning by Yiwen Hu, Tingting Liu, Chenyang Yang, Yuanfang Huang, Shiqiang Suo

Get full text

Enhancing Unmanned Aerial Vehicle Object Detection via Tensor Decompositions and Positive–Negative Momentum Optimizers by Ruslan Abdulkadirov, Pavel Lyakhov, Denis Butusov, Nikolay Nagornov, Dmitry Reznikov, Anatoly Bobrov, Diana Kalita

“…However, the growing number and difficulty of such problems cause the developers to construct machine learning models with higher computational complexities, such as an increased number of hidden layers, epochs, learning rate, and rate decay. …”
Get full text

Optimizing mechanical ventilation: Personalizing mechanical power to reduce ICU mortality - a retrospective cohort study. by Ahmed S Alkhalifah, Kenny Rumindo, Edgar Brincat, Florian Blanchard, Johan Helleberg, David Clarke, Benjamin Popoff, Olivier Duranteau, Zubair Umer Mohamed, Abdelrahman Senosy

“…Statistical analyses and machine learning models, including logistic regression and random forest, were used to predict ICU mortality and establish safe upper limits for IBW-adjusted MP.…”
Get full text

Grey wolf optimization technique with U-shaped and capsule networks-A novel framework for glaucoma diagnosis by Govindharaj I, Ramesh T, Poongodai A, Senthilkumar K. P, Udayasankaran P, Ravichandran S

Get full text

Enhancing MANET Security Through Federated Learning and Multiobjective Optimization: A Trust-Aware Routing Framework by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar, Firoz Bin Yusuf Patel Dawoodi

“…These findings highlight the potential of integrating advanced machine learning and optimization techniques in MANET routing protocols, paving the way for secure, efficient, and adaptive network communications in challenging environments.…”
Get full text

Improved Black-Winged Kite Algorithm with Multi-Strategy Optimization for Identifying <i>Dendrobium huoshanense</i> by Chaochuan Jia, Ting Yang, Maosheng Fu, Yu Liu, Xiancun Zhou, Zhendong Huang, Fang Wang, Wenxia Li

“…Furthermore, the support vector machine (SVM) model was optimized by BKAIM for grade identification of <i>Dendrobium huoshanense</i> based on near-infrared spectral data, thereby confirming its effectiveness in practical applications.…”
Get full text

Optimized CNN-Bi-LSTM–Based BCI System for Imagined Speech Recognition Using FOA-DWT by Meenakshi Bisla, Radhey Shyam Anand

“…The extracted feature vector is fed to the designed CNN-Bi-LSTM classifier such that the EEG data are classified into two-class, three-class, and four-class categories. To achieve optimal performance, the CNN-Bi-LSTM model was optimized using the Keras tuner library. …”
Get full text

Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

“…The proposed hybrid approach enhances feature selection by improving accuracy, reducing computational complexity, and boosting classifier performance. The proposed model, which identifies the optimal feature set for classification using Support Vector Machine (SVM), has achieved an impressive prediction accuracy of 93.94 %. …”
Get full text