[HTML][HTML] Notions of explainability and evaluation approaches for explainable artificial intelligence
Abstract Explainable Artificial Intelligence (XAI) has experienced a significant growth over
the last few years. This is due to the widespread application of machine learning, particularly …
the last few years. This is due to the widespread application of machine learning, particularly …
Explainable artificial intelligence: a systematic review
Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems
IB Aydilek - Applied Soft Computing, 2018 - Elsevier
Optimization in computationally expensive numerical problems with limited function
evaluations provides computational advantages over constraints based on runtime …
evaluations provides computational advantages over constraints based on runtime …
Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems
In recent years, the Intelligent transportations system (ITS) has received considerable
attention, due to higher demands for road safety and efficiency in highly interconnected road …
attention, due to higher demands for road safety and efficiency in highly interconnected road …
A survey on data preprocessing for data stream mining: Current status and future directions
Data preprocessing and reduction have become essential techniques in current knowledge
discovery scenarios, dominated by increasingly large datasets. These methods aim at …
discovery scenarios, dominated by increasingly large datasets. These methods aim at …
[BUKU][B] Data preprocessing in data mining
Data preprocessing is an often neglected but major step in the data mining process. The
data collection is usually a process loosely controlled, resulting in out of range values, eg …
data collection is usually a process loosely controlled, resulting in out of range values, eg …
Multi-head CNN–RNN for multi-time series anomaly detection: An industrial case study
Detecting anomalies in time series data is becoming mainstream in a wide variety of
industrial applications in which sensors monitor expensive machinery. The complexity of this …
industrial applications in which sensors monitor expensive machinery. The complexity of this …