Titlebook: Machine Learning, Optimization, and Big Data; Third International Giuseppe Nicosia,Panos Pardalos,Renato Umeton Conference proceedings 201

onlooker

,A Differential Evolution Algorithm to Develop Strategies for the Iterated Prisoner’s Dilemma, Dilemma (PD) that simulates the selfish behavior between rational individuals. This study investigates the suitability of the DE to evolve strategies for the Iterated Prisoner’s Dilemma (IPD), so that each individual in the population represents a complete playing strategy. Two different approaches

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Forecasting Natural Gas Flows in Large Networks,creased significantly. Accurate forecasting is crucial for maintaining gas supplies, transportation and network stability. This paper presents two methodologies to identify the optimal configuration o parameters of a Neural Network (NN) to forecast the next 24 h of gas flow for each node of a large

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开玩笑

harbinger

Hybrid Global/Local Derivative-Free Multi-objective Optimization via Deterministic Particle Swarm wbility of multi-objective deterministic particle swarm optimization (MODPSO) is combined with the local search accuracy of a derivative-free multi-objective (DFMO) linesearch method. Six MODHA formulations are discussed, based on two MODPSO formulations and three DFMO activation criteria. Forty five

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ORBIT

Multi-objective Genetic Algorithm for Interior Lighting Design,d in lighting design: the respect of a given target level of illuminance, uniformity of lighting, and electrical energy saving. The proposed solution integrates the 3D graphic software Blender, used to reproduce the architectural space and to simulate the effect of illumination, and the genetic algo

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Conference proceedings 2018eld in Volterra, Italy, in September 2017..The 50 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, computational optimization and data science presenting a substantial array of ideas, t

态学

Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models,anslation of different features using examples from cancer literature. We also outline several issues that still arise when assembling cellular network models from state-of-the-art reading engines. Finally, we illustrate the details of our approach with a case study in pancreatic cancer.