Titlebook: Computational Science – ICCS 2021; 21st International C Maciej Paszynski,Dieter Kranzlmüller,Peter M.A. Sl Conference proceedings 2021 Spri

紀(jì)念性

書目名稱Computational Science – ICCS 2021影響因子(影響力)




書目名稱Computational Science – ICCS 2021影響因子(影響力)學(xué)科排名




書目名稱Computational Science – ICCS 2021網(wǎng)絡(luò)公開度




書目名稱Computational Science – ICCS 2021網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Science – ICCS 2021被引頻次




書目名稱Computational Science – ICCS 2021被引頻次學(xué)科排名




書目名稱Computational Science – ICCS 2021年度引用




書目名稱Computational Science – ICCS 2021年度引用學(xué)科排名




書目名稱Computational Science – ICCS 2021讀者反饋




書目名稱Computational Science – ICCS 2021讀者反饋學(xué)科排名

杠桿支點

Fake or Real? The Novel Approach to Detecting Online Disinformation Based on Multi ML Classifiersnment, and sports. This paper presents how ML can be used for detecting fake news. The problem of online disinformation has recently become one of the most challenging issues of computer science. Methods: in this research, a fake news detection method based on multi classifiers (CNN, XGBoost, Random

Grievance

Transformer Based Models in Fake News Detectionl metrics were proposed as a measure of the model quality assessment. Neural network architectures, based on the state-of-the-art solutions of the Transformer type were applied to create the models. The computing capabilities of the Google Colaboratory remote platform, as well as the Flair library,

Optometrist

粗俗人

Bluetooth Low Energy Livestock Positioning for Smart Farming Applicationsation incurs additional requirements and trade-offs that often do not fit into application constraints – use of specific radio technologies, increased communication, computational, and energy costs. This paper presents a localization method that was designed for Smart Farming and applies to a wide r

ROOF

ROOF

A New Multi-objective Approach to Optimize Irrigation Using a Crop Simulation Model and Weather Histigation and water resources for crops is necessary to increase the efficiency of water usage. Many optimization approaches maximize crop yield or profit but do not consider the impact on the environment. We propose a machine learning approach based on the crop simulation model WOFOST to assess the c

linear

Verify

Optimum Design of Tuned Mass Dampers for Adjacent Structures via Flower Pollination Algorithmed as a protective system for adjacent structures that may pound to each other. With a suitable optimization methodology, it is possible to find an optimally tuned TMD that is effective in reducing the responses of structure with an additional protective feature that reduces the amount of required s

Colonnade