Analysis of artificial neural network based on pq-rung orthopair fuzzy linguistic muirhead mean operators DOI

Long Zhou,

Saleem Abdullah,

Hamza Zafar

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127157 - 127157

Published: March 1, 2025

Language: Английский

Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector DOI

Guimei Wang,

Azfarizal Mukhtar, Hossein Moayedi

et al.

Energy, Journal Year: 2024, Volume and Issue: 298, P. 131312 - 131312

Published: April 15, 2024

Language: Английский

Citations

7
An Integrated Approach of Fuzzy AHP-TOPSIS for Multi-Criteria Decision-Making in Industrial Robot Selection DOI Open Access
Ngoc Tien Tran, Van-Long Trinh, C.K. Chung

et al.

Processes, Journal Year: 2024, Volume and Issue: 12(8), P. 1723 - 1723

Published: Aug. 16, 2024

In recent times, industrial robots have gained immense significance and popularity in various industries. They not only enhance labor safety reduce costs but also greatly improve productivity efficiency the production process. However, selecting most suitable robot for a specific process is complex task. There are numerous criteria to consider, often conflicting with each other, making decision-making challenging. order tackle this problem, multi-criteria (MCDM) method employed, which aids ranking decisions based on weights. traditional MCDM methods now considered outdated, researchers concentrating hybrid models that include multiple techniques problems effectively. This study presents an effective model integrates Fuzzy-AHP-TOPSIS evaluate choose best robot. The Fuzzy-AHP utilized establish set of weights evaluation criteria. Subsequently, proposed technique analyzes, prioritizes, chooses option from list factory. experimental results demonstrate by employing integrated fuzzy analytical hierarchy process, taking into account parameter expert judgment, identified worst alternatives factories. outcomes research possess significant implications selection can be applied fields cater requirements.

Language: Английский

Citations

6
Validation of four optimization evolutionary algorithms combined with artificial neural network (ANN) for landslide susceptibility mapping: A case study of Gilan, Iran DOI
Hossein Moayedi, Maochao Xu, Pooria Naderian

et al.

Ecological Engineering, Journal Year: 2024, Volume and Issue: 201, P. 107214 - 107214

Published: Feb. 29, 2024

Language: Английский

Citations

5
AI-driven Protein Engineering for DNA Sequence Modification DOI Creative Commons

Luqi Lin,

Zhengrong Cui, Sihao Wang

et al.

Journal of Theory and Practice of Engineering Science, Journal Year: 2024, Volume and Issue: 4(03), P. 183 - 190

Published: March 25, 2024

The integration of artificial intelligence (AI) with gene editing technologies like CRISPR-Cas9 holds immense promise for advancing biomedical research and personalized medicine. This article highlights the crucial role AI in predicting minimizing off-target effects, thereby enhancing precision efficiency editing. Researchers have developed algorithms BE-DICT to accurately predict base outcomes, showcasing potential AI-driven strategies optimizing processes. By combining bioengineering, this interdisciplinary approach aims automate refine DNA modifications, paving way innovative applications therapy biofabrication. Ultimately, endeavors revolutionize life sciences field, leading significant breakthroughs healthcare biotechnology.

Language: Английский

Citations

5
Assessment of sodium adsorption ratio (SAR) in groundwater: Integrating experimental data with cutting-edge swarm intelligence approaches DOI

Zongwang Wu,

Hossein Moayedi, Marjan Salari

et al.

Stochastic Environmental Research and Risk Assessment, Journal Year: 2024, Volume and Issue: unknown

Published: April 29, 2024

Language: Английский

Citations

5
An integrated fuzzy neural network model for surgical approach selection using double hierarchy linguistic information DOI
Muhammad Nawaz, Saleem Abdullah, Ihsan Ullah

et al.

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 186, P. 109606 - 109606

Published: Dec. 27, 2024

Language: Английский

Citations

5
Intelligent Security Detection and Defense in Operating Systems Based on Deep Learning DOI Creative Commons
Hongbo Wang, Jian Wu, Chenwei Zhang

et al.

International Journal of Computer Science and Information Technology, Journal Year: 2024, Volume and Issue: 2(1), P. 359 - 367

Published: March 24, 2024

With the development of network technology, APT(advanced persistentthreat) attacks are increasing, and research on security enterprise assets requires effective detection digital in space management through screening combing, which is key to real-time monitoring safe operation system. However, accompanying malware also poses a threat user's property privacy, so an method detecting Android necessary. In this direction, although feature processing capability traditional machine learning has been improved, there problems that extraction relies expert experience accuracy low. Therefore, paper combines deep reinforcement technology with operating system detect defend advance, as achieve security.

Language: Английский

Citations

4
Evaluation of student failure in higher education by an innovative strategy of fuzzy system combined optimization algorithms and AI DOI Creative Commons

Junting Nie,

Hossein Ahmadi Dehrashid

Heliyon, Journal Year: 2024, Volume and Issue: 10(7), P. e29182 - e29182

Published: April 1, 2024

This research suggests two novel metaheuristic algorithms to enhance student performance: Harris Hawk's Optimizer (HHO) and the Earthworm Optimization Algorithm (EWA). In this sense, a series of adaptive neuro-fuzzy inference system (ANFIS) proposed models were trained using these methods. The selection best-fit model depends on finding an excellent connection between inputs output(s) layers in training testing datasets (e.g., combination expert knowledge, experimentation, validation techniques). study's primary result is division participants into performance-based groups (failed non-failed). experimental data used build measured fourteen process variables: relocation, gender, age at enrollment, debtor, nationality, educational special needs, current tuition fees, scholarship holder, unemployment, inflation, GDP, application order, day/evening attendance, admission grade. During evaluation, scoring was created addition mean absolute error (MAE), square (MSE), area under curve (AUC) assess efficacy utilized approaches. Further revealed that HHO-ANFIS superior EWA-ANFIS. With AUC = 0.8004 0.7886, MSE 0.62689 0.65598, MAE 0.64105 0.65746, failure pupils assessed with most significant degree accuracy. MSE, MAE, precision indicators showed EWA-ANFIS less accurate, having amounts 0.71543 0.71776, 0.70819 0.71518, 0.7565 0.758. It found optimization have high ability increase accuracy performance conventional ANFIS predicting students' performance, which can cause changes management improve quality academic programs.

Language: Английский

Citations

4
Enhanced IVIFN–ExpTODIM–MABAC Technique for Multi-attribute Group Decision-Making and Applications to College English Teaching Quality Evaluation Under Interval-Valued Intuitionistic Fuzzy Sets DOI
Ge Yang

International Journal of Fuzzy Systems, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Language: Английский

Citations

0
Barriers and enhance strategies for green supply chain management using continuous linear diophantine neural networks DOI Creative Commons
Shougi Suliman Abosuliman, Saleem Abdullah, Noor Ali

et al.

Complex & Intelligent Systems, Journal Year: 2025, Volume and Issue: 11(2)

Published: Jan. 29, 2025

Language: Английский

Citations

0