Learning continuous functions using decision tree learning algorithms by Ibrahim, Ahmed Esmat Mahmoud

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Simultaneous analysis of frequency and voltage control of the interconnected hybrid power system in presence of FACTS devices and demand response scheme by Sudhanshu Ranjan (17151115)

“…The speculated result of the IHPS is presented and analyzed considering real and reactive power as the function of both voltage and frequency. 9The proposed IHPS under investigation has been mathematically modeled for direct coupling like active power–frequency and reactive power–voltage relationships and cross coupling like active power–voltage and reactive power–frequency​ relationships. …”

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

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On-demand deployment of multiple aerial base stations for traffic offloading and network recovery by Sharafeddine, Sanaa

“…We present performance results for the proposed algorithm as a function of various system parameters and demonstrate its effectiveness compared to the close-to-optimal greedy approach and its superiority compared to recent related work from the literature.…”
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Cross entropy error function in neural networks by Nasr, G.E.

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Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) by Kawash, Jalal Y.

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A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. …”
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Properties of simulated annealing and genetic algorithms for mapping data to multicomputers by Mansour, Nashat

“…We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. …”
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Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

“…In this paper, the economic load dispatch (ELD) problem which is an important problem in electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of memetic technique. ELD is tackled by assigning a set of generation units with a minimum fuel costs to generate predefined load demand with accordance to a set of equality and inequality constraints. …”
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Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System by Abualigah, Laith

“…This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. Our approach outperforms existing optimization techniques on benchmark functions, and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision. …”
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A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks by Saad, Walid

“…While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

“…<p dir="ltr">Load balancing is a serious problem in cloud computing that makes it challenging to ensure the proper functioning of services contiguous to the Quality of Service, performance assessment, and compliance to the service contract as demanded from cloud service providers (CSP) to organizations. …”

Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link by Bayan Hussein (16904856)

“…An optimization problem is formulated with data rate and BER in the cost function while maintaining energy and power constraints. …”

An efficient failure-resilient mutual exclusion algorithm for distributed systems leveraging a novel zero-message overlay structure by Mouna Rabhi (17086969)

“…<p>In this paper, we provide a novel failure-resilient token-based mutual exclusion (ME) algorithm for distributed systems. Like a few other solutions in the literature, the proposed solution leverages a logical tree as its underlying topology. …”

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

“…In the next phase, an IRF eliminates the less significant attributes, incorporates a list of decision trees across each iterative process, supervises the classifier’s performance, and prevents overfitting issues. …”

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. …”

A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network by Fareed Ahmad (134672)

Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces by Uzair Sajjad (19646296)

“…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”

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

“…The formulation employs a general objective function that optimizes the total Annual Cost of Energy (ACOE). …”
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Android Malware Detection Using Machine Learning by Al Ali, Shaikha

“…In this work, several machine learning algorithms were utilized, namely k-Nearest neighbor (KNN), Decision Trees (DT), Naive Bayes (NB), Support Vector Machine (SVM) and other ensemble classifiers including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM) and CatBoost. …”
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