4.6 Article

Missing Well Logs Prediction Based on Hybrid Kernel Extreme Learning Machine Optimized by Bayesian Optimization

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Energy & Fuels

Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand

Nahid Sultana et al.

Summary: This study focuses on developing statistical and machine learning approaches for forecasting electricity demand in Ontario. The novel aspects of the study include identifying significant factors affecting electricity consumption, optimizing model hyperparameters using a Bayesian optimization algorithm, and comparing the performance of different models. The results show that the hybrid BOA-NARX model performs well in accurately predicting day-ahead electricity load forecasts.

ENERGIES (2022)

Article Instruments & Instrumentation

Two-round feature selection combining with LightGBM classifier for disturbance event recognition in phase-sensitive OTDR system

Xin Wang et al.

Summary: A novel event recognition method is proposed to tackle with the high nuisance alarm rate in phase-sensitive optical time-domain reflectometer (9-OTDR) system. The light gradient boosting machine (LightGBM) classifier is introduced for multiple event recognition due to its strong interpretability and good performance in multi-classification. Two rounds of feature selection are implemented to improve the recognition efficiency. Experimental results show that the proposed method achieves an average accuracy rate of 97.41% in effectively recognizing five types of disturbance events.

INFRARED PHYSICS & TECHNOLOGY (2022)

Article Computer Science, Interdisciplinary Applications

Student psychology based optimization algorithm: A new population based optimization algorithm for solving optimization problems

Bikash Das et al.

ADVANCES IN ENGINEERING SOFTWARE (2020)

Article Engineering, Mechanical

Integration of deep neural networks and ensemble learning machines for missing well logs estimation

Han Jian et al.

FLOW MEASUREMENT AND INSTRUMENTATION (2020)

Article Computer Science, Artificial Intelligence

Search and rescue optimization algorithm: A new optimization method for solving constrained engineering optimization problems

Amir Shabani et al.

EXPERT SYSTEMS WITH APPLICATIONS (2020)

Article Computer Science, Artificial Intelligence

Efficient boosted grey wolf optimizers for global search and kernel extreme learning machine training

Ali Asghar Heidari et al.

APPLIED SOFT COMPUTING (2019)

Article Computer Science, Information Systems

Supply-Demand-Based Optimization: A Novel Economics-Inspired Algorithm for Global Optimization

Weiguo Zhao et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Fitness Dependent Optimizer: Inspired by the Bee Swarming Reproductive Process

Jaza Mahmood Abdullah et al.

IEEE ACCESS (2019)

Article Computer Science, Artificial Intelligence

A survey on deep learning for big data

Qingchen Zhang et al.

INFORMATION FUSION (2018)

Article Engineering, Electrical & Electronic

Deep Multimodal Learning A survey on recent advances and trends

Dhanesh Ramachandram et al.

IEEE SIGNAL PROCESSING MAGAZINE (2017)

Article Automation & Control Systems

A Competitive Swarm Optimizer for Large Scale Optimization

Ran Cheng et al.

IEEE TRANSACTIONS ON CYBERNETICS (2015)

Article Automation & Control Systems

Extreme Learning Machine for Regression and Multiclass Classification

Guang-Bin Huang et al.

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2012)