AMPSO: A new Particle Swarm Method for Nearest Neighborhood Classification [PDF]
, 2009 Nearest prototype methods can be quite successful on many pattern classification problems. In these methods, a collection of prototypes has to be found that accurately represents the input patterns.
Galván, Inés M. +2 more
core +1 more source
Forecasting of Rainfall in Central Java using Hybrid GSTAR-NN-PSO Model [PDF]
E3S Web of Conferences, 2019 Forecasting of rainfall trends is essential for several fields, such as airline and ship management, flood control and agriculture. The rainfall data were recorded several time simultaneously at a number of locations and called the space-time data ...
Yasin Hasbi +3 more
doaj +1 more source
An Investigation into the Merger of Stochastic Diffusion Search and Particle Swarm Optimisation [PDF]
, 2011 This study reports early research aimed at applying the powerful resource allocation mechanism deployed in Stochastic Diffusion Search (SDS) to the Particle Swarm Optimiser (PSO) metaheuristic, effectively merging the two swarm intelligence algorithms ...
Blackwell, Tim +6 more
core +1 more source
Investigating the mechanical properties of activated alkali high permeability concrete according to the ratio of alkaline activators [PDF]
مدلسازی پیشرفته در مهندسی عمرانThis research investigates the mechanical properties of alkali-activated porous concrete compared to cement-based porous concrete. In this regard, the slag of blast furnaces has been used as the base material for cement, and sodium hydroxide and sodium ...
Amir Zohrabi +2 more
doaj +1 more source
Cogent Engineering, 2021 This paper presents simultaneous radial distribution network reconfiguration and switched capacitor bank allocation to enhance the performance of distribution systems.
Yalew Gebru +3 more
doaj +1 more source
An adaptive soft sensor deterioration evaluation and model updating method for time-varying chemical processes [PDF]
Chemical Industry and Chemical Engineering Quarterly, 2020 Due to the time-varying nature of chemical processes, soft sensor models deteriorate, and data prediction accuracy decreases. To address this problem, an adaptive soft sensor modeling method is proposed that not only evaluates the model deterioration by ...
Li Longhao, Dai Yongshou
doaj +1 more source
A comparative analysis of the application and use of public service obligations in air transport within the EU [PDF]
, 2004 The paper seeks to compare and contrast how different EEA (European Economic Area member states have adopted and made use of the public service obligation (PSO mechanism in air transport.
Williams, George, Pagliari, Romano
core +1 more source
PSO-BP codes for modelling the relationships between the national GDP and nighttime light data
, 2022 PSO-BP codes for modelling the relationships between the national GDP and nighttime light ...
Jiandong Chen (11738962) +1 more
core +1 more source
Monthly precipitation data prediction process of CEEMD-PSO-LSTM combined model.
, 2023 Monthly precipitation data prediction process of CEEMD-PSO-LSTM combined model.
Xinyun Jiang (12481005)
core +1 more source
PSO based Hyperparameter tuning of CNN Multivariate Time- Series Analysis
JOIN: Jurnal Online Informatika, 2022 Convolutional Neural Network (CNN) is an effective Deep Learning (DL) algorithm that solves various image identification problems. The use of CNN for time-series data analysis is emerging.
Agung Bella Putra Utama +3 more
doaj +1 more source