Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Mujahid, S.N.

“…A fuzzy relation between observed/input parameters and required/output characteristics is proposed. A genetic algorithm is developed to obtain optimal process targets. …”
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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

“…A fuzzy relation between observed/input parameters and required/output characteristics is proposed. A genetic algorithm is developed to obtain optimal process targets. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

“…Additionally, the multi-objective genetic algorithm (MOGA) was utilised to extract the most optimal parameters for the injection moulding process, aiming to minimise shear and residual stress and thereby increase the resistance of the final product. …”

An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive by Rahman, M. A.

“…At each operating condition a genetic algorithm (GA) is used to optimize proportional-integral (PI) controller parameters in a closed loop vector control scheme. …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”

Decision trees by Srour, F. Jordan

“…An overview of the basic theory behind decision trees coupled with a summary of binary, multi-way, robust, and optimal decision tree algorithms support social scientists in the use of these supervised machine learning tools for both exploratory and predictive analytic contexts.…”
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Scatter search for protein structure prediction. (c2008) by Kehyayan, Christine Houry

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Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

“…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. We show how our algorithm supports the definition of a budget for alignment computation and also augment it with strategies for meta-heuristic optimization and pruning of the search space. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

“…To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …”

Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain by Farshad Rahimi Ghashghaei (20880995)

“…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. …”

Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering by Saadia Jamil (22045946)

“…This raises basic problems like the need for a dimensionality reduction technique for optimal selection of features, fusing the data of different views, and maintaining the inter- and intra-consensus of the multiview dataset. …”

Fault-Tolerant Network Topologies for Datacenters by Attia, Heba Mahmoud Helal

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On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

“…Computational experiments show that the proposed method has solved most of the instances of the addressed problem to optimality and outperformed the existing metaheuristics, e.g., Simulated Annealing (SA) and Particle Swarm Optimization (PSO). …”

Impact of AI and Dynamic Ensemble Techniques in Enhancing Healthcare Services: Opportunities and Ethical Challenges by Haseeb Javed (18576340)

Optimum Partition of Power Networks Using Singular Value Decomposition and Affinity Propagation by Maymouna Ez Eddin (21633650)

“…From this perspective, this paper proposes an efficient framework for fast and optimal PGP, based on singular value decomposition analysis of the graph's Laplacian. …”

Secrecy Performance of Decode-and-Forward Based Hybrid RF/VLC Relaying Systems by Jaber Al-Khori (16855470)

Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem by Denis Alicic (23073484)

“…<p dir="ltr">This paper addresses the Two-Stage Capacitated Facility Location Problem (TSCFLP), a challenging optimization problem with significant applications in supply chain network design. …”

Enhanced Control of Single-Stage PV-STATCOM Using Hybrid MPPT and Adaptive AHLMS for Power Quality Improvement by Nagwa F. Ibrahim (17334201)

“…It employs a hybrid pelican and perturbs and observe and particle swarm optimization (PSO) based maximum power point tracking (MPPT) algorithm to consistently extract peak power from the PV array. …”

Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids by Khayata, Mohammad Tarek

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A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems by Kandil, Sarah M.

“…The formulation is decomposed into two interdependent sub-problems and solved using a combination of metaheuristic and deterministic optimization techniques. A sample case study is presented to illustrate the performance of the algorithm.…”
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