Showing 2 results for Ecbo Algorithm
L. Mottaghi, A. Kaveh, R. A. Izadifard,
Volume 13, Issue 1 (1-2023)
Abstract
This paper presents a computational framework for optimal design of non-prismatic reinforced concrete box girder bridges. The variables include the geometry of the cross section, tapered length, concrete strength and reinforcement of box girders and slabs. These are obtained by the enhanced colliding bodies optimization algorithm to optimizing the cost and again CO2 emission. Loading and design is based on the AASHTO standard specification. The methodology is illustrated by a three-span continuous bridge. The trade-off between optimal cost and CO2 emission in this type of bridge indicates that the difference of costs, as well as CO2 emissions in the solution with both objectives is less than 1%. However, the optimal variables in the cost objective are different from the variables of CO2 emission objective.
A. Kaveh, A. Beitollahi, N. Khavaninzadeh,
Volume 16, Issue 1 (1-2026)
Abstract
This study develops a synthetic earthquake catalog for Iran (1900–1963) using a deep neural network (DNN) optimized by the Enhanced Colliding Bodies Optimization (ECBO) algorithm. The model, trained on post-1964 instrumental data from the Iranian Seismological Center, incorporates spatial, temporal, and tectonic features to estimate earthquake magnitudes. Statistical indices (MAE = 0.0064; RMSE = 0.3748) and bootstrap uncertainty analysis (±0.18 M) confirm the model’s reliability. The generated catalog provides a data-driven basis for improving seismic hazard assessment and historical seismicity reconstruction across the Iranian plateau.
