# Planning strategies in the energy sector: Integrating bayesian neural networks and uncertainty quantification in scenario analysis & optimization

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/planning-strategies-in-the-energy-sector-integrating-bayesian-neural-networks-2/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Funda Iseri,Halil Iseri,Harsh Shah,Eleftherios Iakovou,Efstratios N. Pistikopoulos |
| Citations | 17 |
| DOI | 10.1016/j.compchemeng.2025.109097 |
| Fields | Engineering |
| Open Access | true |
| OA Status | green |
| OA URL | https://pmc.ncbi.nlm.nih.gov/articles/PMC12381812/ |
| OpenAlex ID | https://openalex.org/W4408539214 |
| PMID | 40881044 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Funda Iseri](https://scholariq.org/researchers/funda-iseri/)
- [Halil Iseri](https://scholariq.org/researchers/halil-iseri/)

## Paper journal

- [Computers & Chemical Engineering](https://scholariq.org/journals/computers-and-chemical-engineering/)

## Paper primary topic

- [Energy Load and Power Forecasting](https://scholariq.org/topics/energy-load-and-power-forecasting/)

## Paper topics

- [Energy Load and Power Forecasting](https://scholariq.org/topics/energy-load-and-power-forecasting/)
- [Reservoir Engineering and Simulation Methods](https://scholariq.org/topics/reservoir-engineering-and-simulation-methods/)
- [Process Optimization and Integration](https://scholariq.org/topics/process-optimization-and-integration/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.