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Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms
The present research examined the potential of two important feature selection methods, Bayesian Networks (BN) and Recursive Feature Elimination...
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Constraint programming for reservoir operation optimization of Bhumibol dam
The modern constraint programming (CP) was adopted to minimize water scarcity and excessive water which are the critical issues in reservoir...
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An application of dynamic programming to local adaptation decision-making
Adaptation decision-making in mountain regions necessitates dealing with uncertainties which are driven by the complex topography and the potential...
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Stable Improved Dynamic Programming Method: An Efficient and Accurate Method for Optimization of Reservoir Flood Control Operation
The optimal algorithm to ensure computational efficiency and accuracy remains to be challenging for the development of robust operation model to...
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An Uncertainty-Based Random Boundary Interval Multi-Stage Stochastic Programming for Water Resources Planning
Given the increasing population growth and rapid global economic development, the conflict between reduced available water resources and increased...
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Evaluation of Flow Resistance using Multi-Gene Genetic Programming for Bed-load Transport in Gravel-bed Channels
Evaluation of flow resistance is necessary for the computation of conveyance capacity in open channels. The significance of the friction factor in...
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Use of gene expression programming to predict reference evapotranspiration in different climatic conditions
Evapotranspiration plays a pivotal role in the hydrological cycle. It is essential to develop an accurate computational model for predicting...
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Modeling and predictive analyses related to piezometric level in an earth dam using a back propagation neural network in comparison on non-linear regression
The objective of the dam safety guidelines and rules is to provide design engineers with information on dam planning, design, construction, operation...
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Multiple linear regression and gene expression programming to predict fracture density from conventional well logs of basement metamorphic rocks
Fracture identification and evaluation requires data from various resources, such as image logs, core samples, seismic data, and conventional well...
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Prediction of Pile Setup for Driven Pipe Piles in Fine-Grained Soils Using Gene Expression Programming
This paper presents the development of a novel model for predicting setup of closed-ended steel pipe (CEP) piles driven in predominantly fine-grained...
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Joint-Probabilistic Double-Sided Random Interval Programming for Booster Optimization in Water Distribution Network
In this paper, a joint-probabilistic double-sided random interval chance-constrained programming (JDRICCP) model was proposed to deal with the random...
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Enhancing permeability prediction in tight and deep carbonate formations: new insights from pore description and electrical property using gene expression programming
The estimation of permeability in carbonate formations remains one of the main challenges in reservoir engineering. Existing literature predominantly...
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Gene expression programming-based multivariate model for earth infrastructure: predicting ultimate bearing capacity of rock socketed shafts in layered soil-rock strata
The evaluation of ultimate bearing capacity (Q u ) of rock socketed shafts (RSSs) is crucial for the design of foundation systems. This study proposes...
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A Bayesian Based Multi-stage Type-2-fuzzy Game and Interval-stochastic Programming Method for Planning Basin Energy-water-climate Nexus System
The contradiction between increasing energy demand, decreasing water availability, and deteriorating ecological environment indicates the urgent...
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Application of gene expression programming for seasonal rainfall forecasting in Western Australia using potential climate indices
This study presents the development of rainfall forecast models using potential climate indices for the Kimberley region of Western Australia, using...
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Determining the drilling mud window by integration of geostatistics, intelligent, and conditional programming models in an oilfield of SW Iran
Accurate knowledge of pore and fracture pressures is essential for drilling wells safely with the desired mud weight (MW). Overpressure occurs when...
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Hybrid models for drought forecasting: Integration of multi pre-processing-data driven approaches and non-linear GARCH time series model
This study introduces two integrated methods to model the short- to long-term droughts in terms of the Standardized Precipitation Index (SPI). In...
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Implementing 4D seismic inversion based on Linear Programming techniques for CO2 monitoring at the Sleipner field CCS site in the North Sea, Norway
This article provides a comprehensive analysis of CO 2 injection monitoring in the Sleipner Field. Ensuring the safe storage and containment of CO 2 in...
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The optimal upper-bound solution for factor of safety of slope by linear programming
A new method is proposed for determining the optimal upper-bound solution for the factor of safety of a slope based on linear programming. Unlike the...
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Evaluation and Interpretation of Blasting-Induced Tunnel Overbreak: Using Heuristic-Based Ensemble Learning and Gene Expression Programming Techniques
Overbreak is a prevalent and detrimental phenomenon in hard rock tunnel excavation that escalates construction costs and compromises tunnel...
