Intelligent computing proceedings of the 2020 Computing Conference. Volume 2 /

This book focuses on the core areas of computing and their applications in the real world. Presenting papers from the Computing Conference 2020 covers a diverse range of research areas, describing various detailed techniques that have been developed and implemented. The Computing Conference 2020, wh...

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Bibliographic Details
Corporate Authors: Computing Conference Online, SpringerLink (Online service)
Other Authors: Arai, Kohei, Kappor, Supriya, Bhatia, Rahul
Format: Conference Proceeding eBook
Language:English
Published: Cham : Springer, 2020.
Cham : 2020.
Series:Advances in intelligent systems and computing ; 1229.
Physical Description:
1 online resource.
Subjects:
Computational intelligence -- Congresses.
Artificial intelligence -- Congresses.
Information technology -- Congresses.
Online Access:SpringerLink - Click here for access
Contents:
  • Intro
  • Editor's Preface
  • Contents
  • Urban Mobility Swarms: A Scalable Implementation
  • 1 Introduction
  • 2 Swarm Behavior and Bicycles Lights
  • 3 Technical Description
  • 3.1 A Decentralized Network of Swarms
  • 3.2 Nodes as Oscillators
  • 3.3 Phase and Light
  • 4 Message Broadcasting and Synchronization
  • 4.1 Protocol
  • 4.2 Algorithm
  • 4.3 Addressing Scheme
  • 4.4 Faulty and Malicious Nodes
  • 5 Circuitry, Prototype Fabrication, and Tests
  • 6 Conclusion
  • References
  • Using AI Simulations to Dynamically Model Multi-agent Multi-team Energy Systems
  • 1 Introduction.
  • 2 Background
  • 3 Methodology
  • 4 Experiments
  • 5 Conclusions
  • References
  • Prediction of Cumulative Grade Point Average: A Case Study
  • 1 Introduction
  • 2 Background Details and Related Work
  • 3 Proposed Approach
  • 3.1 The Ordinary Least Square (OLS) Model
  • 3.2 The ANN Model
  • 3.3 The Adaptive Network Based Fuzzy Inference (ANFIS) Model
  • 4 Results
  • 5 Conclusion
  • References
  • Warehouse Setup Problem in Logistics: A Truck Transportation Cost Model
  • 1 Introduction
  • 2 Proposed Models for Hub Location Problem (HLP)
  • 2.1 Model 1. Unit Cost of Goods Transportation Based Model (UCGTM)
  • 2.2 Model 2. Truck Transportation Cost Based Model (TTCM)
  • 3 Anti-predatory NIA (APNIA)
  • 4 Anti-predatory NIA Based Approach for Solving the HLP
  • 5 Experimental Evaluations
  • 5.1 Real-Life Warehouse Setup Problem (WSP)
  • 5.2 Simulation and Results
  • 6 Analysis of Obtained Results by UCGTM and TTCM
  • 7 Conclusion
  • References
  • WARDS: Modelling the Worth of Vision in MOBA's
  • 1 Introduction
  • 2 Contribution
  • 3 Related Work
  • 3.1 Academic Work
  • 3.2 Industry Standard
  • 3.3 Synthesis
  • 4 Methods
  • 4.1 Dataset.
  • 4.2 Evaluating LoL's Vision Score
  • 4.3 Porting LoL's Vision Score to Dota 2
  • 4.4 Expert Based Dota 2 Ward Score
  • 5 Ward Aggregate Record Derived Score (WARDS)
  • 5.1 Overview to WARDS
  • 5.2 Calculating the ̀̀Optimality'' Score
  • 5.3 Calculating the WARDS
  • 6 Results
  • 6.1 Overview
  • 6.2 Expert vs. Average Player Analysis
  • 6.3 WARDS vs Vision Score Analysis
  • 7 Predicting the WARDS Value
  • 7.1 Predicting WARDS with a Neural Network
  • 7.2 Prediction Analysis
  • 8 Discussion/Conclusions
  • References.
  • Decomposition Based Multi-objectives Evolutionary Algorithms Challenges and Circumvention
  • 1 Introduction
  • 2 Decomposition Based Multi Objective Evolutionary Algorithm (MOEA/D) Framework
  • 3 Scalarizing Functions (SF) Adaptation
  • 4 Weight Generation or Adaptation Mechanisms
  • 5 Different MOEA/D Versions
  • 6 Real World Applications
  • 7 Conclusions
  • References
  • Learning the Satisfiability of Ł-clausal Forms
  • 1 Introduction and Preliminaries
  • 2 Instance Generator
  • 3 Dataset and Features
  • 3.1 Numeric Features
  • 3.2 Features from Graph Representations
  • 4 Results.

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