Strategic optimization of engine performance and emissions with bio-hydrogenated diesel and biodiesel: A RVEA-GRNNs framework by Niti Klinkaew, Attasit Wiangkham, Atthaphon Ariyarit, Prasert Aengchuan, Anupap Pumpuang, Sarunporn Sripratum, Atthaphon Maneedaeng, Jiraphon Srisertpol, Ekarong Sukjit

“…This research bridges critical gaps in combined bio-hydrogenated diesel and biodiesel usage and artificial intelligence-driven biofuel optimization, providing valuable insights for practical implementation in Thailand's agricultural sector.…”
Get full text

Causal contextual bandits with one-shot data integration by Chandrasekar Subramanian, Chandrasekar Subramanian, Balaraman Ravindran, Balaraman Ravindran

Get full text

Convolutional sparse coding network for sparse seismic time-frequency representation by Qiansheng Wei, Zishuai Li, Haonan Feng, Yueying Jiang, Yang Yang, Zhiguo Wang

Get full text

Online Prediction of Concrete Temperature During the Construction of an Arch Dam Based on a Sparrow Search Algorithm–Incremental Support Vector Regression Model by Yihong Zhou, Yu Deng, Fang Wang, Chunju Zhao, Huawei Zhou, Zhipeng Liang, Lei Lei

Get full text

PSO-PID-based optimization and HIL verification method for the rear-mounted linkage adjustment of hilly-mountainous tractors by Yiwei Wu, Chengkang Yao, Mengnan Liu, Jingyun Zhang, Lin Wang, Xiaoxiao Du, Xianghai Yan

Get full text

Optimizing Metro Passenger Flow Prediction: Integrating Machine Learning and Time-Series Analysis with Multimodal Data Fusion by Li Wan, Wenzhi Cheng, Jie Yang

Get full text

A novel approach for breast cancer detection using a Nesterov accelerated adam optimizer with an attention mechanism by Abeer Saber, Tamer Emara, Samar Elbedwehy, Esraa Hassan

Get full text

A Deep Reinforcement Learning-Based Speed Optimization System to Reduce Fuel Consumption and Emissions for Smart Cities by Yıldıray Yiğit, Murat Karabatak

“…Innovative technologies like artificial intelligence, particularly Deep Reinforcement Learning (DRL), play a crucial role in reducing fuel consumption and emissions. …”
Get full text

Reinforcement Learning-Based Augmentation of Data Collection for Bayesian Optimization Towards Radiation Survey and Source Localization by Jeremy Marquardt, Leonard Lucas, Stylianos Chatzidakis

“…Safer and more efficient characterization of radioactive environments requires exploring intelligently, utilizing robotic systems which use smart strategies and physics-based statistical models. …”
Get full text

Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models by Yasmine Gaaloul, Olfa Bel Hadj Brahim Kechiche, Houcine Oudira, Aissa Chouder, Mahmoud Hamouda, Santiago Silvestre, Sofiane Kichou

Get full text

Comparative Analysis of Traditional and Deep Learning Approaches for Underwater Remote Sensing Image Enhancement: A Quantitative Study by Yunsheng Ma, Yanan Cheng, Dapeng Zhang

“…This study compares a multi-scale fusion-enhanced physical model and deep learning algorithms to optimize intelligent processing. The physical model, based on the Jaffe–McGlamery model, integrates multi-scale histogram equalization, wavelength compensation, and Laplacian sharpening, using cluster analysis to target enhancements. …”
Get full text

A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care by Kunal Chandnani, Suryakant Tripathy, Ashutosh Krishna Parbhakar, Kshitij Takiar, Urvi Singhal, P. Sasikumar, S. Maheswari

Get full text

Optimization of Cocoa Pods Maturity Classification Using Stacking and Voting with Ensemble Learning Methods in RGB and LAB Spaces by Kacoutchy Jean Ayikpa, Abou Bakary Ballo, Diarra Mamadou, Pierre Gouton

“…Next, we apply classification algorithms to identify the best performers. These algorithms are then combined via stacking and voting techniques, allowing our model to be optimized by taking advantage of the strengths of each method, thus guaranteeing more robust and precise results. …”
Get full text

Toward lightweight intrusion detection systems using the optimal and efficient feature pairs of the Bot-IoT 2018 dataset by Erman Özer, Murat İskefiyeli, Jahongir Azimjonov

“…Various intrusion detection systems approaches have been proposed previously based on data mining, fuzzy techniques, genetic, neurogenetic, particle swarm intelligence, rough sets, and conventional machine learning. …”
Get full text

AutoML: A systematic review on automated machine learning with neural architecture search by Imrus Salehin, Md. Shamiul Islam, Pritom Saha, S.M. Noman, Azra Tuni, Md. Mehedi Hasan, Md. Abu Baten

Get full text

Enhancing Stock Portfolio Selection with Trapezoidal Bipolar Fuzzy VIKOR Technique with Boruta-GA Hybrid Optimization Model: A Multicriteria Decision-Making Approach by Sunil Kumar Sharma

Get full text

Optimal control of discrete event systems under uncertain environment based on supervisory control theory and reinforcement learning by Yingjun Liu, Fuchun Liu

“…Firstly, we use SCT to gather deliberative planning algorithms with the aim to safe control. Then we convert the supervised system to Markov Decision Process simulation environments that is suitable for optimal algorithm training. …”
Get full text

Equalizer Design: HBOA-DE-trained radial basis function neural networks by Santosh Kumar Das, Satya Ranjan Pattanaik, Pradyumna Kumar Mohapatra, Saroja Kumar Rout, Abdulaziz S. Almazyad, Muhammed Basheer Jasser, Guojiang Xiong, Ali Wagdy Mohamed

Get full text

Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis by Shan Wang, Jiaxiang Li, Xinsheng Xu, Ruiqi Wu, Yuhang Qiu, Xuwen Chen, Zijian Qiao

Get full text

Optimal Allocation of Gas Supply Reliability in Natural Gas Pipeline System Based on Exterior Penalty Function Method by Yueqi LIU, Lei HOU, Shuaishuai TANG, Huai SU, Xingtao LI

“…Optimal allocation of gas supply reliability is an important part of gas supply reliability of natural gas pipeline system.In order to study the optimal allocation scheme of gas supply reliability with the lowest cost,a cost function model based on the gas supply capacity of the pipeline system was constructed.To address the limitation of traditional intelligent optimization algorithms (e.g.…”
Get full text