Neural networks (NNs) and decision trees (DTs) are both popular models of machine
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …

This work proposes a decision tree (DT)-based method for initializing a dendritic neuron
model (DNM). Neural networks become larger and larger, thus consuming more and more …

It is necessary to study different aspects of renewable energy generation, including wind
energy. Wind power is one of the most important green and renewable energy resources …

An approximate logic neuron model (ALNM) based on the interaction of dendrites and the
dendritic plasticity mechanism is proposed. The model consists of four layers: a synaptic …

To construct a strong classifier ensemble, base classifiers should be accurate and diverse.
However, there is no uniform standard for the definition and measurement of diversity. This …

The dendritic neural model (DNM) mimics the non‐linearity of synapses in the human brain
to simulate the information processing mechanisms and procedures of neurons. This …

Nowadays, credit classification models are widely applied because they can help financial
decision‐makers to handle credit classification issues. Among them, artificial neural …

Chemical reaction optimization (CRO) algorithm is a robust metaheuristic by simulating the
process of natural chemical reaction and has been applied for solving numerous realistic …

Crucial for carbon capture, utilization, and storage (CCUS) initiatives and diverse industries,
heat transfer underscores the need for a precise assessment of carbon dioxide (CO 2) and …

Breast cancer is a serious disease across the world, and it is one of the largest causes of
cancer death for women. The traditional diagnosis is not only time consuming but also easily …