Intelligent Fusion of Deep Features for Improved Waste Classification حسب Kashif Ahmad (12592762)

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Detecting COVID-19 From Lung Computed Tomography Images: A Swarm Optimized Artificial Neural Network Approach حسب S. Punitha (17945654)

An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection حسب Abu Zitar, Raed

"…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …"

Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization حسب Hafez, Ishaq

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Cuckoo search for portfolio optimization. (c2014) حسب Medawar, Mohammad Kamal El

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Blood Glucose Regulation Modelling and Intelligent Control حسب Nasar, Nabeel

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Particle swarm optimization approach for protein structure prediction in the 3D HP model حسب Mansour, Nashat

"…In this paper, we present a particle swarm optimization (PSO) based algorithm for predicting protein structures in the 3D hydrophobic polar model. …"
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Squirrel Search Algorithm for Portfolio Optimization حسب Dhaini, Mahdi

"…However, the successes of nature-inspired algorithms in hard computational optimization problems have encouraged researchers to design and apply these algorithms for a variety of optimization problems. …"
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Recent Advances of Chimp Optimization Algorithm: Variants and Applications حسب Daoud, Mohammad Sh.

"…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …"
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A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation حسب Iman M. Hosseini Naveh (16891482)

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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method حسب Amit Kumar Balyan (18288964)

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A new reactive power optimization algorithm حسب Mantawy, A.H.

"…This paper presents an algorithm for optimizing reactive power using particle swarm algorithm. …"
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An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization حسب Majdi Mansouri (16869885)

"…First, an efficient feature selection algorithm based on particle swarm optimization (PSO) is proposed. …"

An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications حسب Abu Zitar, Raed

"…The JAYA algorithm combines the survival of the fittest principle from evolutionary algorithms as well as the global optimal solution attractions of Swarm Intelligence methods. …"
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Metaheuristic Optimization Algorithms for Training Artificial Neural Networks حسب Mansour, Nashat

"…The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. …"
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm حسب Saima Hassan (14918003)

"…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …"

A hybrid Harris Hawks optimizer for economic load dispatch problems حسب Al-Betar, Mohammed Azmi

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A Survey of cuckoo search algorithm: optimizer and new applications حسب Abualigah, Laith

"…Cuckoo search (CS) is an efficient swarm intelligence-based algorithm that has come a long way since its start in 2009. …"
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Multiclass feature selection with metaheuristic optimization algorithms: a review حسب Abu Zitar, Raed

"…Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …"
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…"