Sadaghıanı, Omıd Karımı

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/8274
Name Variants
O.K.Sadaghıanı
O., Sadaghiani
O.,Sadaghıanı
O.K.Sadaghiani
S., Omid Karimi
Sadaghıanı,O.K.
Omid Karimi, Sadaghiani
Sadaghıanı, Omıd Karımı
Omıd Karımı, Sadaghıanı
Sadaghiani,O.K.
Sadaghiani, Omid Karimi
S.,Omid Karimi
S.,Omıd Karımı
Karimi Sadaghiani, Omid
Karimi Sadaghiani,O.
Job Title
Doktor Öğretim Üyesi
Email Address
omid.sadaghiani@atilim.edu.tr
Main Affiliation
Energy Systems Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

2

ZERO HUNGER
ZERO HUNGER Logo

2

Research Products

11

SUSTAINABLE CITIES AND COMMUNITIES
SUSTAINABLE CITIES AND COMMUNITIES Logo

0

Research Products

14

LIFE BELOW WATER
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1

Research Products

6

CLEAN WATER AND SANITATION
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0

Research Products

1

NO POVERTY
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0

Research Products

5

GENDER EQUALITY
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0

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
INDUSTRY, INNOVATION AND INFRASTRUCTURE Logo

0

Research Products

16

PEACE, JUSTICE AND STRONG INSTITUTIONS
PEACE, JUSTICE AND STRONG INSTITUTIONS Logo

0

Research Products

17

PARTNERSHIPS FOR THE GOALS
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0

Research Products

15

LIFE ON LAND
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3

Research Products

10

REDUCED INEQUALITIES
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0

Research Products

7

AFFORDABLE AND CLEAN ENERGY
AFFORDABLE AND CLEAN ENERGY Logo

4

Research Products

8

DECENT WORK AND ECONOMIC GROWTH
DECENT WORK AND ECONOMIC GROWTH Logo

0

Research Products

4

QUALITY EDUCATION
QUALITY EDUCATION Logo

0

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION
RESPONSIBLE CONSUMPTION AND PRODUCTION Logo

4

Research Products

3

GOOD HEALTH AND WELL-BEING
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0

Research Products

13

CLIMATE ACTION
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0

Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

5

Articles

5

Views / Downloads

12/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

27

Scopus Citation Count

39

WoS h-index

3

Scopus h-index

4

Patents

0

Projects

0

WoS Citations per Publication

5.40

Scopus Citations per Publication

7.80

Open Access Source

2

Supervised Theses

0

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JournalCount
Biomass and Bioenergy1
Energy Sources, Part A: Recovery, Utilization, and Environmental Effects1
Energy Technology1
International Journal of Green Energy1
Journal of Material Cycles and Waste Management1
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Author: Peng, WeiSubject: Deep learning

Scholarly Output Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Review
    Citation - WoS: 2
    Citation - Scopus: 5
    Machine Learning for Sustainable Reutilization of Waste Materials as Energy Sources - a Comprehensive Review
    (Taylor & Francis inc, 2024) Peng, Wei; Sadaghiani, Omid Karimi
    This work reviews Machine Learning applications in the sustainable utilization of waste materials as energy source so that analysis of the past works exposed the lack of reviewing study. To solve it, the origin of waste biomass raw materials is explained, and the application of Machine Learning in this section is scrutinized. After analysis of numerous papers, it is concluded that Machine Learning and Deep Learning are widely utilized in waste biomass production areas to enhance the quality and quantity of production, improve the predictions, diminish the losses, as well as increase storage and transformation conditions. The positive effects and application with the utilized algorithms and other effective information are collected in this work for the first time. According to the statistical analysis, in 20% out of the studies conducted about the application of Machine Learning and Deep Learning in waste biomass raw materials, Artificial Neural Network (ANN) algorithm has been applied. Afterward, the Super Vector Machine (SVM) and Random Forest (RF) are the second and third most-utilized algorithms applied in 15% and 14% of studies. Meanwhile, 27% of studies focused on the applications of Machine Learning and Deep Learning in the Forest wastes.
  • Thumbnail Image
    Review
    Citation - WoS: 3
    Citation - Scopus: 5
    A Systematic Review on Smart Waste Biomass Production Using Machine Learning and Deep Learning
    (Springer, 2023) Peng, Wei; Sadaghiani, Omid Karimi
    The utilization of waste materials, as an energy resources, requires four main steps of production, pre-treatment, bio-refinery, and upgrading. This work reviews Machine Learning applications in the waste biomass production step. By investigating numerous related works, it is concluded that there is a considerable reviewing gap in the surveying and collecting the applications of Machine Learning in the waste biomass. To fill this gap with the current work, the kinds and resources of waste biomass as well as the role of Machine Learning and Deep Learning in their development are reviewed. Moreover, the storage and transportation of the wastes are surveyed followed by the application of Machine Learning and Deep Learning in these areas. Summarily, after analysis of numerous papers, it is concluded that Machine Learning and Deep Learning are widely utilized in waste biomass production areas to enhance the waste collecting quality and quality, improve the predictions, diminish the losses, as well as increase storage and transformation conditions.