Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”

Evolutionary algorithm for protein structure prediction by Mansour, Nashat

“…A protein is characterized by its 3D structure, which defines its biological function. The protein structure prediction problem has real-world significance where several diseases are associated with the wrong folding of proteins. …”
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Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

“…In this paper, we present a Scatter Search (SS) algorithm for predicting 3D structures of proteins based on torsion angles representation. …”
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Evolutionary algorithm for predicting all-atom protein structure by Mansour, Nashat

“…We present an improved version of a scatter search (SS) algorithm for predicting all-atoms protein structures using a recent energy model. …”
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Scatter search for protein structure prediction. (c2008) by Kehyayan, Christine Houry

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Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010) by Ghalayini, Iman Adnan

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Particle swarm optimization based algorithm for protein structure prediction in the 3D HP model. (c2008) by Kanj, Fatima Hassan

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Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

“…The proposed algorithm (Ls-AOA) was tested against unimodal and multimodal benchmark functions and demonstrated better capability comparatively using other efficient metaheuristic algorithms reported in the literature. …”

Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

“…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. …”

Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures by Iryna Haponchyk (19691701)

“…Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. …”

Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm by Abdelbasset Krama (16870008)

“…<p dir="ltr">This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. …”

Computational evluation of protein energy functions by Mansour, Nashat

“…In this project, we carry out a computational evaluation of putative protein energy functions. Our findings show that the CHARMM energy model tends to be more appropriate for ab initio computational techniques that predict protein structures. …”
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Evolution Of Activation Functions for Neural Architecture Search by Nader, Andrew

“…However, to the best of our knowledge, the design of new activation functions has mostly been done by hand. In this work, we propose the use of a self-adaptive evolutionary algorithm that searches for new activation functions using a genetic programming approach, and we compare the performance of the obtained activation functions to ReLU. …”
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Software defect prediction. (c2019) by Moussa, Rebecca

“…One that focuses on predicting defect in software modules using a hybrid heuristic - a combination of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
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Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning by Sait, Sadiq M.

“…A series of experiments are performed to evaluate the efficiency of the algorithms. ISCAS-85/89 benchmark circuits are used and experimental results are reported and analyzed to compare the performance of GA, TS and SimE. …”
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Stochastic evolution algorithm for technology mapping by Al-Mulhem, A.S.

“…Experimental results show that SELF-Map has an overall better performance compared to other algorithms reported in the literature…”
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Fragment-based computational protein structure prediction by Mansour, Nashat

“…The method is based on a two-phase Scatter Search algorithm that minimizes the energy function. Backbone fragments are extracted from the Robetta server and side chains are, extracted from the Dunbrack Library. …”
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Fragment based protein structure prediction. (c2013) by Terzian, Meghrig Ohanes

“…In recent years, the protein structure prediction problem has come under extensive investigation, and computational structure prediction methods are circumventing the time-consuming experimental methods by accelerating the prediction process. …”
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Evolutionary algorithms for VLSI multi-objective netlist partitioning by Sait, Sadiq M.

“…A series of experiments are performed to evaluate the efficiency of the algorithms. ISCAS-85/89 benchmark circuits are used and experimental results are reported and analyzed to compare the performance of GA, TS and SimE. …”
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A new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…This paper presents a new genetic algorithm approach to solve the unit commitment problem in electric power systems. …”
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