Computational Intelligence

To obtain the prices of parts from the manufacturing characteristics and other manufacturing processes, feature quantity expression is innovatively applied. By identifying manufacturing features and calculating the feature quantities, the feature quantities are described in the form of assignments as data. To obtain the prices of parts intelligently, the most widely used and mature deep-learning method is adopted to realize the accurate quotation of parts

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  • Computational Intelligence
  • Last Updated On: 
    Tue, 05/21/2019 - 21:42

    This dataset used in the experiment of paper "Bus Ridesharing Scheduling Problem". This is a real-world bus ridesharing scheduling problem of Chengdu city in China, which includes 10 depots, 2,000 trips.

    85 views
  • Transportation
  • Last Updated On: 
    Wed, 05/08/2019 - 09:20

    This is the dataset used in the experiment of paper "Bus Pooling: A Large-Scale Bus Ridesharing Service". The dataset contains 60,822,634 trajectory data from 11,922 Shanghai taxis from one day (Apr 1, 2018). The 100 groups of coordinate sets containing three coordinates as experimental samples are used to compare the effectiveness and efficiency of location-allocation algorithms.

    146 views
  • Transportation
  • Last Updated On: 
    Thu, 05/30/2019 - 07:46

    Bitcoin is a decentralized digital currency that has gained significant attention and growth in recent years. Unlike traditional currencies, Bitcoin does not rely on a centralized authority to control the supply, distribution, and verification of the validity of transactions. Instead, Bitcoin relies on a peer-to- peer network of volunteers to distribute pending transactions and confirmed blocks, verify transactions, and to collectively implement a replicated ledger that everyone agrees on. This peer-to-peer (P2P) network is at the heart of Bitcoin and many other blockchain technologies.

    247 views
  • Communications
  • Last Updated On: 
    Tue, 11/12/2019 - 10:38

    This paper presents a fast and open source extension based on the NSGA-II code stored in the repository of the Kanpur Genetic Algorithms Laboratory (KanGAL) and the adjustment of the selection operator. It slightly modifies existing well-established genetic algorithms for many-objective optimization called the NSGA-III, the adaptive NSGA-III (A-NSGA-III), and the efficient adaptive NSGA-III,  (A$^2$-NSGA-III).

    502 views
  • Computational Intelligence
  • Last Updated On: 
    Wed, 10/16/2019 - 15:00

    A Hybrid Approach to Service Recommendation Based on Network Representation Learning

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  • Computational Intelligence
  • Last Updated On: 
    Mon, 04/08/2019 - 07:38

    A Hybrid Approach to Service Recommendation Based on Network Representation Learning

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  • Computational Intelligence
  • Last Updated On: 
    Mon, 04/08/2019 - 07:38

    A new dataset named Sanitation is released to evaluate the HAR algorithm’s performance and benefit the researchers in this field, which collects seven types of daily work activity data from sanitation workers.We provide two .csv files, one is the raw dataset “sanitation.csv”, the other is the pre-processed features dataset which is suitable for machine learning based human activity recognition methods.

    169 views
  • Computational Intelligence
  • Last Updated On: 
    Mon, 04/01/2019 - 09:52

    Includes sentiment-specific distributed word representations that have been trained on 10M Arabic tweets that are distantly supervised using positive and negative keywords. As described in the paper [1], we follow Tang’s [2] three neural architectures, which encode the sentiment of a word in addition to its semantic and syntactic representation. 

     

    Specifications Table

    Subject area

     Natural Language Processing

    26 views
  • Computational Intelligence
  • Last Updated On: 
    Fri, 03/29/2019 - 09:02

    The dataset contains measurements taken from four air handling units (AHU) installed in a medium-to-large size academic building. The building is a 7-story, 9000 sqm facility commissioned in 2016 hosting the PRECIS research center. It contains multiple research laboratories, multifunction spaces, meeting rooms, and a large auditorium as well as administrative offices. It is located at 44°2606.0N and 26°0244.0E in a temperate continental climate with hot summers and cold winters. Cooling is handled using on-site electric chillers while heating is provided from a district heating network.

    516 views
  • Computational Intelligence
  • Last Updated On: 
    Fri, 03/15/2019 - 09:51

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