[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
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 deep …
years. This is due to the widespread application of machine learning, particularly deep …
Recent trends in the use of statistical tests for comparing swarm and evolutionary computing algorithms: Practical guidelines and a critical review
A key aspect of the design of evolutionary and swarm intelligence algorithms is studying
their performance. Statistical comparisons are also a crucial part which allows for reliable …
their performance. Statistical comparisons are also a crucial part which allows for reliable …
[HTML][HTML] Landslide susceptibility mapping using machine learning: A literature survey
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …
occur more frequently due to increasing urbanization, deforestation, and climate change …
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
A Boukerche, Y Tao, P Sun - Computer networks, 2020 - Elsevier
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 …
[图书][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 …