Zobrazeno 1 - 10
of 248
pro vyhledávání: '"Naser, A. Z."'
Autor:
Naser, Ahmed Z, Naser, MZ
This paper introduces a new addition to the SPINEX (Similarity-based Predictions with Explainable Neighbors Exploration) family, tailored specifically for time series and forecasting analysis. This new algorithm leverages the concept of similarity an
Externí odkaz:
http://arxiv.org/abs/2408.02159
Autor:
Naser, MZ, Naser, Ahmed Z
This article introduces an expansion within SPINEX (Similarity-based Predictions with Explainable Neighbors Exploration) suite, now extended to single, multiple, and many objective optimization problems. The newly developed SPINEX-Optimization algori
Externí odkaz:
http://arxiv.org/abs/2408.02155
Autor:
Naser, M. Z., Naser, A. Z.
This paper presents the Firefighter Optimization (FFO) algorithm as a new hybrid metaheuristic for optimization problems. This algorithm stems inspiration from the collaborative strategies often deployed by firefighters in firefighting activities. To
Externí odkaz:
http://arxiv.org/abs/2406.00528
Autor:
Naser, MZ, Naser, Ahmed Z
This paper presents a novel anomaly and outlier detection algorithm from the SPINEX (Similarity-based Predictions with Explainable Neighbors Exploration) family. This algorithm leverages the concept of similarity and higher-order interactions across
Externí odkaz:
http://arxiv.org/abs/2407.04760
Autor:
Naser, M. Z., al-Bashiti, Mohammad Khaled, Tapeh, Arash Teymori Gharah, Eslamlou, Armin Dadras, Naser, Ahmed, Kodur, Venkatesh, Hawileeh, Rami, Abdalla, Jamal, Khodadadi, Nima, Gandomi, Amir H.
In the rapidly evolving optimization and metaheuristics domains, the efficacy of algorithms is crucially determined by the benchmark (test) functions. While several functions have been developed and derived over the past decades, little information i
Externí odkaz:
http://arxiv.org/abs/2406.09581
Machine learning (ML)-based solutions are rapidly changing the landscape of many fields, including structural engineering. Despite their promising performance, these approaches are usually only demonstrated as proof-of-concept in structural engineeri
Externí odkaz:
http://arxiv.org/abs/2404.12544
This communication presents preliminary findings from comparing two recent chatbots, OpenAI's ChatGPT and Google's Bard, in the context of fire engineering by evaluating their responses in handling fire safety related queries. A diverse range of fire
Externí odkaz:
http://arxiv.org/abs/2403.04795
The field of machine learning (ML) has witnessed significant advancements in recent years. However, many existing algorithms lack interpretability and struggle with high-dimensional and imbalanced data. This paper proposes SPINEX, a novel similarity-
Externí odkaz:
http://arxiv.org/abs/2306.01029
Autor:
Naser, M. Z.
Causal diagrams are logic and graphical tools that depict assumptions about presumed causal relations. Such diagrams have proven effective in tackling a variety of problems in social sciences and epidemiology research yet remain foreign to civil engi
Externí odkaz:
http://arxiv.org/abs/2306.15834
Autor:
Naser, M. Z., Ross, Brandon, Ogle, Jennier, Kodur, Venkatesh, Hawileh, Rami, Abdalla, Jamal, Thai, Huu-Tai
The engineering community has recently witnessed the emergence of chatbot technology with the release of OpenAI ChatGPT-4 and Google Bard. While these chatbots have been reported to perform well and even pass various standardized tests, including med
Externí odkaz:
http://arxiv.org/abs/2303.18149