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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 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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
ProbC: joint modeling of epigenome and transcriptome effects in 3D genome
(BioMed Central Ltd, 2022-12)
Background: Hi-C and its high nucleosome resolution variant Micro-C provide a window into the spatial packing of a genome in 3D within the cell. Even though both techniques do not directly depend on the binding of specific ...
A new deep learning restricted boltzmann machine for energy consumption forecasting
(MDPI, 2022-08)
A key issue in the desired operation and development of power networks is the knowledge of load growth and electricity demand in the coming years. Mid-term load forecasting (MTLF) has an important rule in planning and ...
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, ...
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