Semi-supervised multi-task learning based framework for power system security assessment by Muhy Eddin Za’ter, Amir Sajadi, Bri-Mathias Hodge

“…Additionally, this framework incorporates a confidence measure for its predictions, enhancing its reliability and interpretability. …”
Get full text

Automatic Detection of Occluded Main Coronary Arteries of NSTEMI Patients with MI-MS ConvMixer + WSSE Without CAG by Mehmet Cagri Goktekin, Evrim Gul, Tolga Çakmak, Fatih Demir, Mehmet Ali Kobat, Yaman Akbulut, Ömer Işık, Zehra Kadiroğlu, Kürşat Demir, Abdulkadir Şengür

“…Moreover, to maximise the classifier performance, the WSSE algorithm was developed to adjust the classification prediction value according to the feature importance weights. …”
Get full text

GEOGRAPHICALLY WEIGHTED MACHINE LEARNING MODEL FOR ADDRESSING SPATIAL HETEROGENEITY OF PUBLIC HEALTH DEVELOPMENT INDEX IN JAVA ISLAND by Muhammad Azis Suprayogi, Bagus Sartono, Khairil Anwar Notodiputro

“…Random Forest (RF) machine learning models have emerged as a prominent algorithm, addressing problems arising from the sole use of decision trees, such as overfitting and instability. …”
Get full text

AI-Driven Optimization of Multilayer Thin-Film Structures for Advanced Optical Applications by Emad Alkhazraji, Sani Mukhtar, Haitham Khaled, Jaime Viegas

“…Finally, we integrate the surrogate model with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) multi-objective optimization algorithm to maximize both the transmission peak and its full width at half maximum (FWHM) for a desired wavelength band. …”
Get full text

Ensemble deep learning-enabled single-shot composite structured illumination microscopy (eDL-cSIM) by Jiaming Qian, Chunyao Wang, Hongjun Wu, Qian Chen, Chao Zuo

“…Experimental results demonstrate that eDL-cSIM integrates the advantages of various state-of-the-art neural networks, enabling robust super-resolution image predictions across different specimen types or structures of interest, and outperforms classical physics-driven methods in terms of imaging speed, reconstruction quality and environmental robustness, while avoiding intricate and specialized algorithmic procedures. …”
Get full text

An Innovative Online Adaptive High-Efficiency Controller for Micro Gas Turbine: Design and Simulation Validation by Rui Yang, Yongbao Liu, Xing He, Zhimeng Liu

“…To evaluate the performance changes of the gas turbine, we applied deep learning techniques to enhance the extreme learning machine (ELM) algorithm, resulting in the development of a high-precision, high-real-time deep extreme learning machine (DL_ELM) prediction model. …”
Get full text

Improving computational drug repositioning through multi-source disease similarity networks by Duc-Hau Le

“…We applied a tailored Random Walk with Restart (RWR) algorithm to predict novel drug-disease associations. …”
Get full text

Amortized Fairness for Drive-Thru Internet by Zhi Li, Limin Sun, Xinyun Zhou

“…The amortized fairness MAC requires predictions of future link quality. For this, we fully exploit the inner and inter-AP correlations revealed from our extensive field studies and design a link quality prediction algorithm. …”
Get full text

A PCC-Ensemble-TCN model for wind turbine icing detection using class-imbalanced and label-missing SCADA data by Shenyi Ding, Zhijie Wang, Jue Zhang, Fang Han, Xiaochun Gu, Guangxiao Song

“…Temporal convolutional networks are trained to extract features and make predictions on each subset. The final prediction result is obtained by ensembling the prediction results of all temporal convolutional network models. …”
Get full text

Load–Settlement Modeling of Micropiled Rafts in Cohesive Soils Using an Artificial Intelligence Technique by Ahmed Elsawwaf, Hany El Naggar

“…To advance the adoption of micropiles in geotechnical practice, this study employs a multi-objective genetic algorithm-based evolutionary polynomial regression (EPR-MOGA), a hybrid artificial intelligence method, to develop a robust and straightforward model for predicting the load–settlement response of micropiled rafts in cohesive soils under vertical loads. …”
Get full text

Wind Power Installed Capacity Forecast Based on a Two-Parameter Variable-Weight Buffer Operator and Subsidy Strategy Research by Ye Li, Xue Bai

“…Firstly, a new two-parameter variable-weight buffer operator is proposed to quantify the impact of the policy shock, whose optimal parameters are obtained by the genetic algorithm, and combined with the grey GM(1,1) model to predict the installed capacity of wind power in China under the cessation of subsidy policy. …”
Get full text

Deep Neural Network for Supervised Single-Channel Speech Enhancement by Nasir SALEEM, Muhammad IRFAN KHATTAK, Muhammad Yousaf ALI, Muhammad SHAFI

“…The trained network predicts the coefficients to construct a ratio mask based on mean square error (MSE) objective cost function. …”
Get full text

Pixels relationship analysis for extracting building footprints by A. Emelyanov, A. Emelyanov, V. Knyaz, V. Knyaz, V. Kniaz, V. Kniaz, D. Artist

“…Currently, remote sensing research is focused on developing an automated algorithm that can compete with empirical methods for mapping the contours of individual buildings. …”
Get full text

Exploring replay by Georgy Antonov, Peter Dayan

“…They therefore need to explore. However, the algorithmic structure of exploratory choices in the brain still remains largely elusive. …”
Get full text

Using machine learning to simultaneously quantify multiple cognitive components of episodic memory by Soroush Mirjalili, Audrey Duarte

“…Using a machine learning algorithm known as “transfer learning”, we leveraged visual perception, sustained attention, and selective attention brain states to better predict episodic memory performance from trial-to-trial encoding electroencephalography (EEG) activity. …”
Get full text

Research on lightweight malware classification method based on image domain by SUN Jingzhang, CHENG Yinan, ZOU Binghui, QIAO Tonghua, FU Sizheng, ZHANG Qi, CAO Chunjie

“…Firstly, a CBG algorithm was introduced to solve the problems of imbalanced image sizes and excessive noise in malware images. …”
Get full text

HR Management Big Data Mining Based on Computational Intelligence and Deep Learning by Genliang Zhao, Zhe Xue

“…To this end, this paper proposes an end-to-end competency-aware job requirement generation framework to automate the job requirement generation, and the prediction based on competency themes can realize the skill prediction in job requirements. …”
Get full text

Simulation of the Performance of a Centrifugal Chiller by Luo Yi, Zhang Libiao, Hang Bingbing, Gong Chengcheng

“…The simulation software successfully predicts various parameters, such as chilled water temperatures, cooling water temperatures, and flow rates of the centrifugal chiller under different loads.…”
Get full text

A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment. by Tao Yu, Wei Huang, Xin Tang, Duosi Zheng

“…Furthermore, a multi-view combined unsupervised method is designed to thoroughly mine data and enhance the robustness of label predictions. This method mitigates discrepancies in prediction outcomes from three distinct perspectives. …”
Get full text

Hand segmentation pipeline from depth map: an integrated approach of histogram threshold selection and shallow CNN classification by Zhengze Xu, Wenjun Zhang

“…We found that MINIMUM, MEAN and MEDIAN are effective ways to separate objects and the threshold in the valley between two maxima similar to MINIMUM algorithm with a minimum error. Then, each segmentation proposal is evaluated by a 3-layers shallow convolutional neural network (CNN) which is trained as a binary classification function to predict whether it is a partition of hand. …”
Get full text