Analysis of power consumer behavior based on the complementation of K-means and DBSCAN
L Zhang, S Deng, S Li - … on energy internet and energy system …, 2017 - ieeexplore.ieee.org
With the rapid growth of China's economy, different areas of electricity behavior diversity.
Traditionally, the K-means algorithm divides each data in the dataset into corresponding …
Traditionally, the K-means algorithm divides each data in the dataset into corresponding …
A self adaptive harmony search based functional link higher order ANN for non-linear data classification
In the data classification process involving higher order ANNs, it'sa herculean task to
determine the optimal ANN classification model due to non-linear nature of real world …
determine the optimal ANN classification model due to non-linear nature of real world …
A novel honey-bees mating optimization approach with higher order neural network for classification
In the recent past, several biological and natural phenomena have extensively attracted
researchers towards the rapid development of science and engineering. Basically solving …
researchers towards the rapid development of science and engineering. Basically solving …
A novel FLANN with a hybrid PSO and GA based gradient descent learning for classification
In this paper, it is an attempt to design a PSO & GA based FLANN model (PSO-GA-FLANN)
for classification with a hybrid Gradient Descent Learning (GDL). The PSO, GA and the …
for classification with a hybrid Gradient Descent Learning (GDL). The PSO, GA and the …
A honey bee mating optimization based gradient descent learning–FLANN (HBMO-GDL-FLANN) for Classification
Motivated from successful use of the Honey Bee Mating Optimization (HMBO) in many
applications, in this paper, a HMBO based Gradient Descent Learning for FLANN classifier …
applications, in this paper, a HMBO based Gradient Descent Learning for FLANN classifier …
A harmony search based gradient descent learning-FLANN (HS-GDL-FLANN) for classification
Abstract The Harmony Search (HS) algorithm is meta-heuristic optimization inspired by
natural phenomena called musical process and it quite simple due to few mathematical …
natural phenomena called musical process and it quite simple due to few mathematical …
[HTML][HTML] A global-best harmony search based gradient descent learning FLANN (GbHS-GDL-FLANN) for data classification
While dealing with real world data for classification using ANNs, it is often difficult to
determine the optimal ANN classification model with fast convergence. Also, it is laborious to …
determine the optimal ANN classification model with fast convergence. Also, it is laborious to …
Nonlinear time series forecasting using a novel self-adaptive TLBO-MFLANN model
S Panigrahi, HS Behera - International Journal of …, 2019 - inderscienceonline.com
In this paper, we have proposed a multiplicative FLANN (MFLANN) model for time series
forecasting. In addition, an improved version of teaching learning based optimisation …
forecasting. In addition, an improved version of teaching learning based optimisation …
Solving nonlinear classification problems with black hole optimisation and higher order Jordan Pi-sigma neural network: a novel approach
Nature inspired optimisation algorithms have been on a leading focus of all researchers
since last few decades. Successful applications of such algorithms for solving diversified …
since last few decades. Successful applications of such algorithms for solving diversified …
An efficient FLANN model with CRO-based gradient descent learning for classification
Due to the nonlinear nature of real world data, it is difficult to determine the optimal ANN
classification model with accurate and fast convergence. Although, many higher order ANN …
classification model with accurate and fast convergence. Although, many higher order ANN …