A Real Data-Driven Analytical Model to Predict Happiness
نویسندگان
چکیده
منابع مشابه
Developing a Fuzzy Logic Model to Predict Asphaltene Precipitation during Natural Depletion based on Experimental Data
متن کامل
A model to predict the sequential behavior of healthy blood donors using data mining
This article has no abstract.
متن کاملBeyond Analytical Modeling, Gathering Data to Predict Real Agents’ Strategic Interaction
This paper presents research proposals on the interdisciplinary research infrastructure for understanding human reasoning in game-theoretic terms. Strategic reasoning impacts human decision making in social, economical and competitive interactions. The provided introduction summarizes concepts from AI, game theory and psychology. First result is a concept of interdisciplinary game description l...
متن کاملHITIQA: A Data Driven Approach to Interactive Analytical Question Answering
In this paper we describe the analytic question answering system HITIQA (High-Quality Interactive Question Answering) which has been developed over the last 2 years as an advanced research tool for information analysts. HITIQA is an interactive open-domain question answering technology designed to allow analysts to pose complex exploratory questions in natural language and obtain relevant infor...
متن کاملAnalytical Model and Data-driven Approach for Concrete Moisture Prediction
The advent of smart sensing technologies has opened up new avenues for addressing the billion dollar problem in the wastewater industry of H2S corrosion in concrete sewer pipes, where there is a growing interest in monitoring the environmental properties that govern the rate of corrosion. In this context, this paper proposes a methodology to predict the moisture content of concretes through dat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scholars journal of physics, mathematics and statistics
سال: 2021
ISSN: ['2393-8064', '2393-8056']
DOI: https://doi.org/10.36347/sjpms.2021.v08i03.001