Search Results - "boosting algorithms"

Data-driven machine learning approach for predicting dwell fatigue life in two classes of Titanium alloys by Rahman, Syed Abdur, Chandraker, Abhinav, Prakash, Om, Chauhan, Ankur

“…[Display omitted] •GBOOST and XGBOOST ML algorithms were utilized to predict dwell fatigue lives in two classes of Titanium alloys.•Addition of synthetic data…”
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Boosting methods for multi-class imbalanced data classification: an experimental review by Tanha, Jafar, Abdi, Yousef, Samadi, Negin, Razzaghi, Nazila, Asadpour, Mohammad

“…Since canonical machine learning algorithms assume that the dataset has equal number of samples in each class, binary classification became a very challenging…”
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Modelling biochemical oxygen demand in a large inland aquaculture zone of India: Implications and insights by Nagaraju, T. Vamsi, Sri Bala, G., Bonthu, Sridevi, Mantena, Sireesha

“…Water quality surveillance is tough, and a specific timely management is necessary for the inland aquaculture ponds and ecology as well. Real time quality…”
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Optimized Gas Sensor Array with AI for Distinguishing and Classifying Similar Odorants by Cava, Carlos Eduardo, Sun, Helin, Huang, Shirong, Cuniberti, Gianaurelio

“…This study presents a novel approach for odorant classification by integrating advanced machine learning techniques with an electronic nose (e-nose) system…”
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Crystal structural prediction of perovskite materials using machine learning: A comparative study by Priyadarshini, Rojalina, Joardar, Hillol, Bisoy, Sukant Kishoro, Badapanda, Tanmaya

“…In this study, Machine Learning (ML) techniques have been exploited to classify the crystal structure of ABO3 perovskite compounds. In the present work, seven…”
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Unleashing the Potential of Boosting Techniques to Optimize Station-Pairs Passenger Flow Forecasting by Patel, Madhuri, Patel, Samir B., Swain, Debabrata, Shah, Siddharth

“…Station-pair passenger flow forecast modeling is crucial for public transportation to address emerging needs. The accurate prediction and estimation will…”
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Advanced computational models for accurate fracture toughness prediction in diverse concrete types: Insights from a robust laboratory database by Samadi, Hanan, Mahmoodzadeh, Arsalan, Mohammadi, Mokhtar, Alghamdi, Abdulaziz, Ghazouani, Nejib, Ahmed, Mohd

“…•Employment a comprehensive dataset including vital material and environmental factors.•Powerful ML framework enables precise fracture toughness prediction in…”
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A hybrid model based on bidirectional long short-term memory neural network and Catboost for short-term electricity spot price forecasting by Zhang, Fan, Fleyeh, Hasan, Bales, Chris

“…Electricity price forecasting plays a crucial role in a liberalised electricity market. Generally speaking, long-term electricity price is widely utilised for…”
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Data-driven Security Assessments for Predicting Information Security Maturity Levels by Muhammad, Alva Hendi, Hanafi, Hanafi, Ari Yuana, Kumara, Ghozali, Bahrun, Haris, Ruby

“…This study investigates the use of machine learning to improve Information Security Risk Assessment (ISRA), with a particular emphasis on the KAMI framework,…”
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Recognition of human activities for wellness management using a smartphone and a smartwatch: A boosting approach by Tarafdar, Pratik, Bose, Indranil

“…Mobile health applications are considered to be powerful tools for activity-based wellness management. With the availability of multimodal sensors in smart…”
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An iterative boosting-based ensemble for streaming data classification by Bertini Junior, João Roberto, Nicoletti, Maria do Carmo

“…•The IBS ensemble bases on iteratively applying boosting to learn from data stream.•IBS adjusts to new concept by gathering knowledge according to its current…”
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Short-term forecasting of emergency medical services demand exploring machine learning by Shahidian, Nika, Abreu, Paulo, Santos, Daniel, Barbosa-Povoa, Ana

“…This study addresses the challenge of forecasting short-term demand in Emergency Medical Services (EMS) using machine learning techniques, which is essential…”
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Prediction of nonlinear dynamic responses and generation of seismic fragility curves for steel moment frames using boosting machine learning techniques by Zareian, Farzaneh, Banazadeh, Mehdi, Zareian, Mohammad Sajjad

“…•Four boosting machine learning (ML) models were developed to predict the seismic responses of steel moment frames.•The maximum global and interstory drift…”
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Optimizing Epileptic Seizure Recognition with Machine Learning Algorithms by Sanagavarupu Sunitha

“…According to the WHO, Epilepsy is a significant public health issue and increases every year from 1% to 2% in all age groups. It is one of the oldest…”
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Assessing the performance of state-of-the-art machine learning algorithms for predicting electro-erosion wear in cryogenic treated electrodes of mold steels by Cetin, Abdurrahman, Atali, Gokhan, Erden, Caner, Ozkan, Sinan Serdar

“…•Accurate machine learning models minimize delays and losses in manufacturing.•Cryogenically treated electrodes boost EDM wear prediction accuracy.•Identified…”
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Design of concrete-filled steel tubular columns using data-driven methods by Degtyarev, Vitaliy V., Thai, Huu-Tai

“…By leveraging the merits of structural steel and concrete materials, concrete-filled steel tubular (CFST) structures have been increasingly used in the…”
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Assessing industrial wastewater effluent toxicity using boosting algorithms in machine learning: A case study on ecotoxicity prediction and control strategy development by Nguyen, Duc-Viet, Park, Jihae, Lee, Hojun, Han, Taejun, Wu, Di

“…Trace heavy metals have a tendency to persist in the effluent of industrial wastewater treatment facilities, leading to toxic effects on downstream water…”
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Performance evaluation of boosting machine learning algorithms for lithofacies classification in heterogeneous carbonate reservoirs by Al-Mudhafar, Watheq J., Abbas, Mohammed A., Wood, David A.

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Diabetes classification model based on boosting algorithms by Chen, Peihua, Pan, Chuandi

“…Background Diabetes mellitus is a common and complicated chronic lifelong disease. Hence, it is of high clinical significance to find the most relevant…”
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MQTTEEB-D: A high-fidelity benchmark for real-time MQTT anomaly detection using machine learning techniques by Allaga, Hamza, Biniz, Mohamed, Farchane, Abderrazak

“…Message Queuing Telemetry Transport (MQTT) is essential for resource-constrained Internet of Things (IoT) environments; however, its widespread adoption has…”
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