Browsing Scopus İndeksli Yayınlar Koleksiyonu by Subject "Machine learning"
Now showing items 1-14 of 14
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Android Malware Detection Using Machine Learning
(Institute of Electrical and Electronics Engineers Inc., 2020)The usage of mobile devices is increasing exponentially. There were lots of critical applications such as banking to health applications are available on mobile devices through mobile applications. This penetration and ... -
Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review
(Elsevier, 2022)The goal of managing smart cities and societies is to maximize the efficient use of finite resources while enhancing the quality of life. To establish a sustainable urban existence, smart cities use some new technologies ... -
Click prediction boosting via Bayesian hyperparameter optimization-based ensemble learning pipelines
(Elsevier B.V., 2023)Online travel agencies (OTA's) advertise their website offers on meta-search bidding engines. The problem of predicting the number of clicks a hotel would receive for a given bid amount is an important step in the management ... -
A Comparative Application of Machine Learning Approaches to Win-back Lost Customers
(Institute of Electrical and Electronics Engineers Inc., 2023)Today's consumer is more knowledgeable and conscious than in the past. For this reason, it is quite possible for consumers to leave their service/product providers and start receiving service from another service/product ... -
A comparative study of surrogate based learning methods in solving power flow problem
(IEEE, 2020)Due to increasing volume of measurements in smart grids, surrogate based learning approaches for modeling the power grids are becoming popular. This paper uses regression based models to find the unknown state variables ... -
Forecasting the Short-Term Electricity In Steel Manufacturing For Purchase Accuracy on Day-Ahead Market
(Institute of Electrical and Electronics Engineers Inc., 2022)Forecasting electricity consumption in the most accurate way is crucial for purchase on the day-ahead market in steel manufacturing. This study is aimed to predict short-term electricity consumption regarding the day-ahead ... -
The Geothermal Artificial Intelligence for geothermal exploration
(Pergamon-Elsevier Science Ltd, 2022)Exploration of geothermal resources involves analysis and management of a large number of uncertainties, which makes investment and operations decisions challenging. Remote Sensing (RS), Machine Learning (ML) and Artificial ... -
How to engage consumers through effective social media use-guidelines for consumer goods companies from an emerging market
(Universidad de Talca, 2021-07)This study aims to establish actionable guidelines and provide strategic insights as a means of increasing the social media effectiveness of consumer brands. Post-related factors in addition to the contextual and temporal ... -
Machine learning applications for COVID-19 outbreak management
(Springer London Ltd, 2022)Recently, the COVID-19 epidemic has resulted in millions of deaths and has impacted practically every area of human life. Several machine learning (ML) approaches are employed in the medical field in many applications, ... -
Machine Learning Approaches for Predicting Protein Complex Similarity
(Mary Ann Liebert Inc Publ, 2017)Discriminating native-like structures from false positives with high accuracy is one of the biggest challenges in protein-protein docking. While there is an agreement on the existence of a relationship between various ... -
Machine learning model for maternal quality in sheep
(Organising Committee of the 9th European Conference on Precision Livestock Farming (ECPLF), Teagasc, Animal and Grassland Research and Innovation Centre, 2019)This paper aims to identify determinant traits of ewes by measuring their impact on lamb survival. For that, we devised a machine learning model that correlates ewe traits to lamb survival, and figured out as to which ewe ... -
Random CapsNet forest model for imbalanced malware type classification task
(Elsevier, 2021)Behavior of malware varies depending the malware types, which affects the strategies of the system protection software. Many malware classification models, empowered by machine and/or deep learning, achieve superior ... -
Ranking Protein-Protein Binding Using Evolutionary Information and Machine Learning
(Association for Computing Machinery, 2017)Discriminating native-like complexes from false-positives with high accuracy is one of the biggest challenges in protein-protein docking. The relationship between various favorable intermolecular interactions (e.g. Van ... -
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...