2
The trinity of COVID-19: immunity, inflammation and intervention
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Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy
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Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)
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Estimating Risk for Death from Coronavirus Disease, China, January–February 2020
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One world, one health: The novel coronavirus COVID-19 epidemic
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A self-adaptive virus optimization algorithm for continuous optimization problems
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Stock Market Prediction Using Optimized Deep-ConvLSTM Model
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Un mundo, una salud: la epidemia por el nuevo coronavirus COVID-19
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Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study
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Recurrent Neural Network Training using ABC Algorithm For Traffic Volume Prediction
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Deep Learning on Big, Sparse, Behavioral Data
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Transforming Finance Into Vision: Concurrent Financial Time Series as Convolutional Nets
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Review of Meta-Heuristic Optimization based Artificial Neural Networks and its Applications
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Particle swarm optimization of deep neural networks architectures for image classification
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Auto Tuning of RNN Hyper-parameters using Cuckoo Search Algorithm
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Bio-inspired computation: Where we stand and what's next
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A survey of swarm and evolutionary computing approaches for deep learning
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Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting
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Midterm Power Load Forecasting Model Based on Kernel Principal Component Analysis and Back Propagation Neural Network with Particle Swarm Optimization
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Deep learning framework to forecast electricity demand
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Multi-step forecasting for big data time series based on ensemble learning
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Network Traffic Prediction Based on LSTM Networks with Genetic Algorithm
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Genetic Algorithm-Optimized Long Short-Term Memory Network for Stock Market Prediction
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A scalable approach based on deep learning for big data time series forecasting
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Using ant colony optimization to optimize long short-term memory recurrent neural networks
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Scalable Forecasting Techniques Applied to Big Electricity Time Series
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Learnheuristics: hybridizing metaheuristics with machine learning for optimization with dynamic inputs
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Simulating SIR processes on networks using weighted shortest paths
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A novel metaheuristic for continuous optimization problems: Virus optimization algorithm
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A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting
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Evolving Deep Recurrent Neural Networks Using Ant Colony Optimization
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Estimating the basic reproductive ratio for the Ebola outbreak in Liberia and Sierra Leone
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A survey on optimization metaheuristics
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Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)
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Understanding individual human mobility patterns
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Methods for Estimating the Case Fatality Ratio for a Novel, Emerging Infectious Disease
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THE WORLD HEALTH ORGANIZATION
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Ebola virus disease. Technical report
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Immunity passports in the context of COVID-19. Technical report
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Coronavirus disease 2019 (COVID-19): Situation report 74. Technical report
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Korea Centers for Disease
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Artificial Bee Colony-Optimized LSTM for Bitcoin Price Prediction
49
Handbook of Metaheuristics
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Middle East respiratory syndrome coronavirus (MERS-CoV). Technical report
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A New Optimized Cuckoo Search Recurrent Neural Network (CSRNN) Algorithm
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Consensus document on the epidemiology of severe acute respiratory syndrome (SARS)
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This parameter simulates the duration of the pandemic
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This probability simulates how an infected individual can travel to any place in the world and can infect any healthy individual.
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New infected population
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known that a recovered individual can be re-infected
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Some of the infected individuals die. They die according to the coronavirus death rate ( P DIE ). For simplicity, it is considered that such individuals cannot infect new individuals
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Another relevant contribution of this work is the proposal of a new codification, discrete and of dynamic length, specifically designed for hybridizing LSTM with CVOA (or any other metaheuristic)
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Sensitivity Analysis section
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MERS obtained the poorest results in terms of fitness but it explored a smaller space search
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parameter values lead to results varying both in fitness and in execution time
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4) New infected populations, on the contrary, are different for each strain and no concurrent operations are required
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algorithm: a bioinspired metaheuristic based on the COVID-19 propagation model
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Each infected individual has a probability of dying ( P DIE ), according to the COVID-19 death rate. Such individuals cannot spread the disease to new individuals
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The individuals who do not die will cause infection to new individuals (intensification)
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CVOA can stop the solutions exploration after several iterations, with no need to be configured
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The number of individuals evaluated increases at each iteration on an almost linear basis, as the number of strains increases. In case no random numbers were generated, the