Prediction of status particulate matter 2.5 using state Markov chain stochastic process and HYBRID VAR-NN-PSO
Air pollution is the entry or inclusion of living things, energy substances, and other
components into the air. Moreover, Air pollution is the presence of one or several …
components into the air. Moreover, Air pollution is the presence of one or several …
[PDF][PDF] Employing best input SVR robust lost function with nature-inspired metaheuristics in wind speed energy forecasting
Wind power has been experiencing a quick improvement. Without a doubt, wind is a
variable asset that is hard to forecast. For instance, traditionally time series, extra holds are …
variable asset that is hard to forecast. For instance, traditionally time series, extra holds are …
Optimizing extreme learning machine for drought forecasting: water cycle vs. bacterial foraging
Machine learning (ML) methods have shown noteworthy skill in recognizing environmental
patterns. However, presence of weather noise associated with the chaotic characteristics of …
patterns. However, presence of weather noise associated with the chaotic characteristics of …
Optimisation‐based training of evolutionary convolution neural network for visual classification applications
Training of the convolution neural network (CNN) is a problem of global optimisation. This
study proposed a hybrid modified particle swarm optimisation (MPSO) and conjugate …
study proposed a hybrid modified particle swarm optimisation (MPSO) and conjugate …
A time-varying stock portfolio selection model based on optimized PSO-BiLSTM and multi-objective mathematical programming under budget constraints
J Vaziri, D Farid, M Nazemi Ardakani… - Neural Computing and …, 2023 - Springer
Choosing the optimal portfolio is an ongoing challenging research area and a complex
process involving selecting the best investment plan according to various factors, such as …
process involving selecting the best investment plan according to various factors, such as …
A Novel Real-Time PV Error Handling Exploiting Evolutionary-Based Optimization
A Dimara, A Papaioannou, K Grigoropoulos… - Applied Sciences, 2023 - mdpi.com
The crucial need for perpetual monitoring of photovoltaic (PV) systems, particularly in remote
areas where routine inspections are challenging, is of major importance. This paper …
areas where routine inspections are challenging, is of major importance. This paper …
Optimal placement of viscous wall dampers in RC moment resisting frames using metaheuristic search methods
Viscous wall dampers (VWDs) are one of the most effective energy dissipation devices for
the seismic performance enhancement of buildings. The number of VWDs as well as their …
the seismic performance enhancement of buildings. The number of VWDs as well as their …
Human Activity Prediction using Long Short Term Memory
Early symptoms of dementia is one of the causes decrease in quality of life. Human activity
recognition (HAR) system is proposed to recognize the daily routines which has an …
recognition (HAR) system is proposed to recognize the daily routines which has an …
[PDF][PDF] Graphical interface of genetic optimization in neural network modelling for time series
Various gradient based optimization techniques have been developed for optimizing neural
network weights. However, the stability of results in obtaining the optimal weights has …
network weights. However, the stability of results in obtaining the optimal weights has …
MFI-PSO: A flexible and effective method in adversarial image generation for deep neural networks
Deep neural networks (DNNs) have achieved great success in image classification, but can
be very vulnerable to adversarial attacks with small perturbations to images. To improve …
be very vulnerable to adversarial attacks with small perturbations to images. To improve …