[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 …
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 …
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 …
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 social learning particle swarm optimization algorithm for scalable optimization
Social learning plays an important role in behavior learning among social animals. In
contrast to individual (asocial) learning, social learning has the advantage of allowing …
contrast to individual (asocial) learning, social learning has the advantage of allowing …
[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 …