Browsing by Subject "Machine learning"
Now showing items 1-20 of 20
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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 ... -
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 ... -
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 ... -
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 ... -
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 ... -
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 ... -
Human movement recognition with dynamic movement primitives
(2015-09)Dynamic Movement Primitives (DMPs)-originally a method for movement trajectory generation has been also used for recognition tasks. However there has not been a systematic comparison between other recognition methods and ... -
Incremental analysis of large-scale system logs for anomaly detection
(IEEE, 2019)Anomalies during system execution can be detected by automated analysis of logs generated by the system. However, large scale systems can generate tens of millions of lines of logs within days. Centralized implementations ... -
MaLeFICE: Machine learning support for continuous performance improvement in computational engineering
(Wiley, 2022-04-25)Computer aided engineering (CAE) practices improved drastically within the last decade due to ease of access to computing resources and open-source software. However, increasing complexity of hardware and software settings ... -
Minimizing false positive rate for DoS attack detection: A hybrid SDN-based approach
(Elsevier, 2020-06)Denial of Service attacks (DoS) are considered to be a major threat against today's communication networks. Recently, a novel networking paradigm that provides enhanced programming abilities has been proposed to attain an ... -
A platform for personal e-mobility with route forecasting
(IEEE, 2020)This study reports a new e-mobility platform to construct effective usage of charging points by electric vehicle users to eliminate long charge durations. The e-mobility platform includes such subsystems as smartphones, ... -
A platform for personal e-mobility with route forecasting
(2021-01-14)Decreasing fossil fuel sources and increasing carbon exhaust rate makes human-beings lead to search on different technological fields and to develop new technology. Also, thanks to developing tendency to the clean energy ... -
Polarity classification of twitter messages using audio processing
(Elsevier, 2020-11)Polarity classification is one of the most fundamental problems in sentiment analysis. In this paper, we propose a novel method, Sound Cosine Similaritye Matching, for polarity classification of Twitter messages which ... -
Using machine learning tools for forecasting natural gas consumption in the province of Istanbul
(Elsevier, 2019-05)Commensurate with unprecedented increases in energy demand, a well-constructed forecasting model is vital to managing energy policies effectively by providing energy diversity and energy requirements that adapt to the ... -
Validating android permission requests by analyzing APP descriptions
(2016-07)Android applications can access sensitive user data if they are granted certain permissions. Android security model gives users the responsibility to approve permission requests of applications. For this, a user needs to ...
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