Browsing by Subject "Machine learning"
Now showing items 1-20 of 37
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An actor-critic reinforcement learning approach for bilateral negotiation
Designing an effective and intelligent bidding strategy is one of the most compelling research challenges in automated negotiation, where software agents negotiate with each other to find a mutual agreement when there is ... -
Advancing home healthcare through machine learning: Predicting service time for enhanced patient care
(IEEE, 2023)Providing healthcare services at home is crucial for patients who require long-term care or face mobility or other health-related constraints that prevent them from traveling to healthcare facilities. Effective data analysis ... -
Allocating costs in a lot sizing game using novel machine learning methods
In supply chain management (SCM), effective resource utilization is the key to achieving certain strategic benefits such as minimizing costs, increasing service levels, reducing inventories, increasing responsiveness, and ... -
An applicable approach to automate customer complaints
Customer complaint management is critical and time-consuming process for institutions. For an effective management and increased customer satisfaction, developing an instant and automated reply mechanism is essential. This ... -
An application for a particleboard plant: Web-based decision support system for quality prediction and digital transformation
As it is same for most of the production procedures, a certain quality level must be derived in the particle board production. In the particleboard production, a series of samples taken from the production line for the ... -
Automated defect prioritization based on defects resolved at various project periods
(Elsevier, 2021-09)Defect prioritization is mainly a manual and error-prone task in the current state-of-the-practice. We evaluated the effectiveness of an automated approach that employs supervised machine learning. We used two alternative ... -
Big data–enabled sign prediction for Borsa Istanbul intraday equity prices
(Elsevier, 2023-12)This paper employs a big data source, the Borsa Istanbul's “data analytics” information, to predict 5-min up, down, and steady signs drawn from closing price changes. Seven machine learning algorithms are compared with ... -
Comparative study of credit risk evaluation for unbalanced datasets using deep learning classifiers
(IEEE, 2023)Credit risk assessment deals with calculating the risk of a loan not being repaid. For this reason, a lot of research effort is directed at credit risk analysis. In this study, machine learning models such as Light ... -
A data-driven matching algorithm for ride pooling problem
(Elsevier, 2022-04)This paper proposes a data-driven matching algorithm for the problem of ride pooling, which is a transportation mode enabling people to share a vehicle for a trip. The problem is considered as a variant of matching problem, ... -
DiBLIoT: A distributed blacklisting protocol for iot device classification using the hashgraph consensus algorithm
(IEEE Computer Society, 2022)Industrial applications require highly reliable, secure, low-power and low-delay communications. However, wireless communication links in the industrial environment suffer from various channel impairments which can compromise ... -
DILAF: A framework for distributed analysis of large-scale system logs for anomaly detection
(Wiley, 2019-02)System logs constitute a rich source of information for detection and prediction of anomalies. However, they can include a huge volume of data, which is usually unstructured or semistructured. We introduce DILAF, a framework ... -
Disentangling human trafficking types and the identification of pathways to forced labor and sex: an explainable analytics approach
(Springer, 2023-07)Terms such as human trafficking and modern-day slavery are ephemeral but reflect manifestations of oppression, servitude, and captivity that perpetually have threatened the basic right of all humans. Operations research ... -
A distributed blacklisting protocol for iot device classification using the hashgraph consensus algorithm
Industrial applications require highly reliable, secure, low-power and low-delay communications. However, wireless communication links in the industrial environment suffer from various channel impairments which can compromise ... -
Evaluation of distributed machine learning algorithms for anomaly detection from large-scale system logs: a case study
(IEEE, 2018)Anomaly detection is a valuable feature for detecting and diagnosing faults in large-scale, distributed systems. These systems usually provide tens of millions of lines of logs that can be exploited for this purpose. ... -
Evaluation of linguistic and prosodic features for detection of Alzheimer’s disease in Turkish conversational speech
(Springer Science+Business Media, 2015-12)Automatic diagnosis and monitoring of Alzheimer’s disease can have a significant impact on society as well as the well-being of patients. The part of the brain cortex that processes language abilities is one of the earliest ... -
An explainable credit scoring framework: A use case of addressing challenges in applied machine learning
(IEEE, 2022)While Machine Learning (ML) classification algorithms can accurately classify a borrower's credit risk, the determinants of the credit score cannot be interpreted clearly by customers, decision makers and auditors. The ... -
Explorations on inverse reinforcement learning for the analysis of motor control and cognitive decision making mechanisms of the brain
Reinforcement Learning is a framework for generating optimal policies given a task and a reward/punishment structure. Likewise, Inverse Reinforcement Learning, as the name suggests, is used for recovering the reasoning ... -
Feature extraction for enhancing data-driven urban building energy models
(European Council on Computing in Construction (EC3), 2023)Building energy demand assessment plays a crucial role in designing energy-efficient building stocks. However, most studies adopting a data-driven approach feel the deficiency of datasets with building-specific information ... -
Finecloud: Fine-grained cloud service advisory using machine learning
(IEEE, 2022)Motivated by real customer problems, we investigated utilization of cloud services at different layers including infrastructure (IaaS), application services (PaaS) and databases (DaaS). We found several issues such as ... -
A healthcare inventory problem with both reliable and unreliable supply channels
(2016-05)In this study, we investigate the inventory review policy for a healthcare facility to minimize the impact of inevitable drug shortages when an alternative reliable supplier is present. A continuous-time stochastic process ...
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