Binary Multi-Objective Grey Wolf Optimizer for Feature Selection in Classification
نویسندگان
چکیده
منابع مشابه
Binary grey wolf optimization approaches for feature selection
In this work, a novel binary version of the grey wolf optimization (GWO) is proposed and used to select optimal feature subset for classification purposes. Grey wolf optimizer (GWO) is one of the latest bioinspired optimization techniques, which simulate the hunting process of grey wolves in nature. The binary version introduced here is performed using two different approaches. In the first app...
متن کاملGrey Wolf Optimizer
This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, the three main steps of hunting, searching for prey, enc...
متن کاملDistributed multi-agent Load Frequency Control for a Large-scale Power System Optimized by Grey Wolf Optimizer
This paper aims to design an optimal distributed multi-agent controller for load frequency control and optimal power flow purposes. The controller parameters are optimized using Grey Wolf Optimization (GWO) algorithm. The designed optimal distributed controller is employed for load frequency control in the IEEE 30-bus test system with six generators. The controller of each generator is consider...
متن کاملA Modified Grey Wolf Optimizer by Individual Best Memory and Penalty Factor for Sonar and Radar Dataset Classification
Meta-heuristic Algorithms (MA) are widely accepted as excellent ways to solve a variety of optimization problems in recent decades. Grey Wolf Optimization (GWO) is a novel Meta-heuristic Algorithm (MA) that has been generated a great deal of research interest due to its advantages such as simple implementation and powerful exploitation. This study proposes a novel GWO-based MA and two extra fea...
متن کاملMulti Objective Artificial Immune System Weighted Feature Selection for Classification
Supervised learning algorithm based on an AIS using clonal selection is already proposed [1]. Even though some AIS for classification have been developed, an artificial immune system for classification with local feature selection model has a unique feature; it includes the local feature selection mechanism. The aim of feature selection is to reduce the dimension of the input vector by the sele...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.3000040