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Artificial Neural Networks and Particle Swarm Optimization Algorithms for Preference Prediction in Multi-Criteria Recommender Systems

Mohamed Hamada, Mohammed Hassan
2018 Informatics  
This article presents a methodological framework that trains artificial neural networks with particle swarm optimization algorithms and uses the neural networks for integrating the multi-criteria rating  ...  The proposed neural network-based multi-criteria recommender system is integrated with k-nearest neighborhood collaborative filtering for predicting unknown criteria ratings.  ...  Mohamed Hamada is the research advisor, who proposed the structure of the paper and helped in proofreading and improving the quality of the article.  ... 
doi:10.3390/informatics5020025 fatcat:cu6s5glrnjgm5nzqooqkoow3me

Optimization Theory, Methods, and Applications in Engineering

Jung-Fa Tsai, John Gunnar Carlsson, Dongdong Ge, Yi-Chung Hu, Jianming Shi
2012 Mathematical Problems in Engineering  
optimization, stochastic optimization, particle swarm optimization, neural network, simulated annealing, genetic algorithm, and hybrid methods.  ...  In light of advances in computing systems, optimization approaches have become one of the most promising techniques for engineering applications.  ...  optimization, stochastic optimization, particle swarm optimization, neural network, simulated annealing, genetic algorithm, and hybrid methods.  ... 
doi:10.1155/2012/759548 fatcat:3wkb26nllfgp7hf347b3eoox4y

Visual Classification of Music Style Transfer Based on PSO-BP Rating Prediction Model

Tianjiao Li, Wei Wang
2021 Complexity  
to as the PSO-BP rating prediction model, by combining the features of global optimization of particle swarm optimization algorithm, and make further improvements based on the traditional collaborative  ...  Although recommendation systems have been well developed in real applications, the limitations of CF algorithms are slowly coming to light as the number of people increases day by day, such as the data  ...  BP Neural Network and Particle Swarm Optimization Algorithm Analysis 3.1. Neural Network Structure.  ... 
doi:10.1155/2021/9959082 fatcat:tlo6eqfuvvhj5dpbmdkwjfyqwq

Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs

Cristian Rotaru, Octav Brudaru
2012 2012 IEEE Congress on Evolutionary Computation  
This paper presents a cellular genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The evolution process is inspired by a basic genetic algorithm.  ...  The extensive experimental evaluation uses difficult classical benchmarks and proves the efficiency and the stability of the algorithm.  ...  for Neural Networks 247, Glenn Francis and Sandra Stein, Prediction of Histologic Grade in Breast Cancer using an Artificial Neural Network. 266, Yozo Suzuki, Michimasa Kitahara and Masaki Kobayashi,  ... 
doi:10.1109/cec.2012.6256590 dblp:conf/cec/RotaruB12 fatcat:4ly3nrktw5habc6lf5err7d5py

A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

Abdul Shah, Haidawati Nasir, Muhammad Fayaz, Adidah Lajis, Asadullah Shah
2019 Information  
The gaps in the literature are due to advancements in technology, the drawbacks of optimization algorithms, and the introduction of new optimization algorithms.  ...  In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes.  ...  Programming (ADHDP), Neural Network, Backpropagation (BP), Particle Swarm Optimization (PSO).  ... 
doi:10.3390/info10030108 fatcat:7n53fwv3mzbqhfdi6oqvgetnny

Optimal Travel Route Recommendation Mechanism Based on Neural Networks and Particle Swarm Optimization for Efficient Tourism Using Tourist Vehicular Data

Malik, Kim
2019 Sustainability  
The algorithms used in the proposed methodology are neural networks for prediction and particle swarm optimization for finding the optimal route.  ...  In this work, we propose an optimal route recommendation mechanism for the prediction of the next tourist attraction and optimal route recommendation to the predicted tourist attraction.  ...  Artificial Neural Networks The research work carried out in [40] resulted in shifting the focus to the study of artificial intelligence-based neural networks.  ... 
doi:10.3390/su11123357 fatcat:hs7b772hdbgm3ieakjqzdwfqxa

Applied Metaheuristic Optimization in Asphalt Pavement Management

Luis Ricardo Vásquez-Varela, Francisco Javier García-Orozco
2021 Ciencia e Ingeniería Neogranadina  
Pavement management requires powerful optimization tools for multi-objective problems such as minimizing costs and maximizing the pavement state from network to project level with constrained budgets.  ...  There are multiple applications of optimization algorithms in pavement engineering, emphasizing pavement management for its socioeconomic implications and back-calculation of layer properties for its complexity  ...  Qian [27] improved several performance prediction models for pavements by hybridizing a genetic algorithm and an artificial neural network.  ... 
doi:10.18359/rcin.4371 fatcat:yvtls7poszcifh6yurnjcm4lti

Computation Methods for the Diagnosis and Prognosis of Heart Disease

Deepthi S, Aswathy Ravikumar
2014 International Journal of Computer Applications  
Artificial Neural Network using hybrid algorithm for optimization (ANN-GSO-ABC, 2014) In ANN-GSO-ABC method, to strengthen the training process of the artificial neural network to predict the heart disease  ...  In Predictive Risk Assessment of Arthrosclerosis (PRAA) approach, an imputation algorithm and particle swarm optimization (PSO) is used to predict the risk factors associated.  ...  PRAA is a novel approach which is used for the prediction of risk factor based on an in-built imputation algorithm and Particle Swarm Optimization technique.  ... 
doi:10.5120/16700-6832 fatcat:poofheen3ndl7btzrpqugt657i

Computational Intelligence Techniques with Application to Crude Oil Price Projection: A Literature Survey from 2001- 2012

H. Chiroma, S. Abdulkareem, A. Abubakar, M. Joda Usman
2013 Neural Network World  
It is expected that researchers across the globe may thus be encouraged to re-direct their attention and resources in order to keep on searching for an optimum solution.  ...  This paper is an attempt to survey the applications of computational intelligence techniques for predicting crude oil prices over a period of ten years.  ...  [11] who hybridized genetic algorithms, particle swarm optimization and ant colony optimization. Fazel and Gamasaee [12] integrated fuzzy logic and expert systems. Jia et al.  ... 
doi:10.14311/nnw.2013.23.032 fatcat:35opoiffefggpgbyxbj4cxhsnu

The neural paradigm for complex systems: new algorithms and applications

Stefano Squartini, Jinhu Lu, Qinglai Wei
2011 Neural computing & applications (Print)  
Lan et al., where a particle swarm optimization-based approach is presented for optimal sitting and sizing of aggregator controlled public car park for electric vehicle (EVs) fleets in modern power system  ...  This special issue focuses on new hot topics in the field of Neural Networks for Complex Systems including new algorithms and applications.  ... 
doi:10.1007/s00521-011-0713-4 fatcat:ww5yp7ewd5bs7muhoeos4ip4wu

Incorporate Cost Matrix into Learning Vector Quantization Modeling: a Comparative Study of Genetic Algorithm, Simulated Annealing and Particle Swarm Optimization

Ning Chen, Bernardete Ribeiro, Armando Vieira, Joao Duarte, Joao C. Neves
2011 Journal of clean energy technologies  
Comparatively, genetic algorithm appears to be able to obtain superior solutions to particle swarm optimization and simulated annealing for optimizing the neural network.  ...  In [31] , the appropriateness of SA and GA as global search algorithms is investigated in optimizing the neural network.  ... 
doi:10.7763/ijcte.2011.v3.293 fatcat:uzjtbp3wevhv3nfxhib7orleju

Household appliance usage recommendation based on demand forecasting and multi­objective optimization

Allan Rivalles Souza Feitosa, Henrique Figuerôa Lacerda, Wellington Pinheiro dos Santos, Abel Guilhermino da Silva Filho
2022 Research, Society and Development  
Multi­objective optimization techniques such as Non­Sorted Genetic Algorithm II (NSGA II), Multi­Objective Particle Swarm Optimization (MOPSO), Speed constrained Multi-­objective Particle Swarm Optimization  ...  (SMOPSO), and Strength Pareto Evolutionary Algorithm two (SPEA2), for example, were tested for the Recommendation Module.  ...  Multi-Objective Particle Swarm Optimization (Nebro et al., 2009) , and Strength Pareto Evolutionary Algorithm 2 (Zitzler et al., 2001) .  ... 
doi:10.33448/rsd-v11i1.24515 fatcat:uwwdiayppvecvonil23gwvzz7m

Determination of industrial energy demand in Turkey using MLR, ANFIS and PSO-ANFIS

2021 Journal of Artificial Intelligence and Systems  
In this study, Multiple Linear Regression (MLR), Adaptive Neuro-Fuzzy Inference System (ANFIS), and optimized ANFIS with Particle Swarm Optimization (PSO) methods are employed to forecast energy demand  ...  The coefficient of determination (R 2 ) for PSO-ANFIS, MLR, and ANFIS models are 0.9951, 0.9889, and 0.9932 in the training stage, and 0.9423, 0.9181, and 0.8776 in the testing stage, respectively.  ...  Journal of Artificial Intelligence and Systems While each individual is looking for the PSO solution (particle), a swarm is known as the particles' population.  ... 
doi:10.33969/ais.2021.31002 fatcat:3rs4iuesa5flhgnzsoxrmczf2q

Hot Strip Mill Transportation in Rourkela Steel Plant

Rajat Kumar Panigrahy, R. K. Mishra, Srikanta Patnaik
2011 International Journal of Instrumentation Control and Automation  
This paper discussed possible adaptation of electronic transport means in Hot Strip Mill for improving finished product quality. The present system operating in Rourkela steel plant is discussed.  ...  Particle Swarm Optimization (PSO): It is a powerful and effective optimization method, similar in some ways to Genetic Algorithms (GA) and other evolutionary algorithms.  ...  Therefore, stochastic optimization schemes like particle swarm optimization (PSO) [2] or its variants shall be preferred in this scenario.  ... 
doi:10.47893/ijica.2011.1002 fatcat:e4ya7eayrrhh7oydir6jnphuhi

A survey on multi-objective hyperparameter optimization algorithms for Machine Learning [article]

Alejandro Morales-Hernández and Inneke Van Nieuwenhuyse and Sebastian Rojas Gonzalez
2021 arXiv   pre-print
This article presents a systematic survey of the literature published between 2014 and 2020 on multi-objective HPO algorithms, distinguishing between metaheuristic-based algorithms, metamodel-based algorithms  ...  We also discuss the quality metrics used to compare multi-objective HPO procedures and present future research directions.  ...  Evolving deep neural networks by multi-objective particle swarm optimization for image classification.  ... 
arXiv:2111.13755v2 fatcat:q2qtofihtzev5mose5aj7odfzm
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