English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Planners in construction accordingly have been trying to predict productivity which is a significant criterion for construction performances prior to commencement of operations. Many various methods solely based on deterministic calculations, simulation techniques, statistic methods, or other decision making tools, have been introduced so far. In terms of application, however, these methods depending on one estimation tool have several limitations of each method. The present study presented new predictive models: 1) Model A, combining simulation and a multiple regression (MR) technique, a general estimation technique based on statistic concepts and 2) Model B combining simulation and an artificial neural network (ANN) technique, a powerful tool for prediction in engineering basis. Quantified reliability comparisons between actual and predicted productivity data by the presented models were conducted in this study. It found that a predictive result by Model B was closer to actual productivity data...

journal of civil engineering and management

TECHNICAL COMPARISONS OF SIMULATION-BASED PRODUCTIVITY PREDICTION METHODOLOGIES BY MEANS OF ESTIMATION TOOLS FOCUSING ON CONVENTIONAL EARTHMOVINGS / IMITACINIŲ PRODUKTYVUMO PROGNOZAVIMO METODIKŲTECHNINIS PALYGINIMAS, PASITELKUS VERTINIMO PRIEMONES, AKCENTUOJANTŲPRASTUS ŽEMĖS DARBUS