Design and simulation of superdirective adaptive antenna arrays by Dawoud, M.M.

“…These characteristics were made possible by means of both amplitude and phase variations, based on predetermined optimized array polynomials. The commonly used adaptive algorithms were compared and the LMS (least mean square) algorithm was selected for the simulation of the adaptive array system. …”
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Developing a Cooperative Behavior for Multi Agents System Application to Robot Soccer by Idlan, Ayman Hashim

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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

“…<p>Machine learning algorithms have been intensively applied to perform load forecasting to obtain better accuracies as compared to traditional statistical methods. …”

Estimating Vehicle State by GPS/IMU Fusion with Vehicle Dynamics by Saadeddin, Kamal Mohamad

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Bootstrap-based Aggregations and their Stability in Feature Selection by Salman, Reem Elfatih

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The maximum common subgraph problem by Abu-Khzam, Faisal N.

“…With its plethora of applications, MCS is a familiar and challenging problem. Many algorithms exist that can deliver optimal MCS solutions, but whose asymptotic worst-case run times fail to do better than mere brute-force, which is exponential in the order of the smaller graph. …”
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

“…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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A Stochastic Newton-Raphson Method with Noisy Function Measurements by Saab, Khaled Kamal

“…This article proposes a novel recursive algorithm providing optimal iterative-varying gains associated with the NR method. …”
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Parameterization and compensation of friction forces using geneticalgorithms by Al-Duwaish, H.N.

“…A PI controller with parameters optimized using genetic algorithms is used to control the position of a DC motor with friction. …”
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Experimental evaluation of multi-agent reinforcement learning in real-world scale-free networks by Al Hashimi, Rashid

“…Multi-agent reinforcement learning is a common method for optimizing agents' local decision in a distributed and scalable manner. …”
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Scatter search for homology modeling by Mansour, Nashat

“…To improve homology based PSP, we propose a scatter search (SS) metaheuristic algorithm. SS is an evolutionary approach that is based on a population of candidate solutions. …”
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Scatter search metaheuristic for homology based protein structure prediction. (c2015) by Stamboulian, Mouses Hrag

“…To improve homology based PSP, we propose a scatter search (SS) metaheuristic algorithm. Our algorithm optimizes the initial poor alignments, generated by a dynamic programming method. …”
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Complexities of special matrix multiplication problems by Takche, J.

“…This paper develops optimal algorithms to multiply an n × n symmetric tridiagonal matrix by: (i) an arbitrary n × m matrix using 2nm − m multiplications; (ii) a symmetric tridiagonal matrix using 6n − 7 multiplications; and (iii) a tridiagonal matrix using 7n −8 multiplications. …”
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Joint Planning of Smart EV Charging Stations and DGs in Eco-Friendly Remote Hybrid Microgrids by Shaaban, Mostafa

“…The planning problem jointly allocates and sizes a set of distributed generators (DGs) along with the EV charging stations to balance the supply with the total demand of regular loads and EV charging. The planning algorithm specifies optimal locations and sizes of the EV charging stations and DG units that minimize two conflicting objectives: (a) deployment and operation costs and (b) associated green house gas emissions, while satisfying the microgrid technical constraints. …”
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A method for data path synthesis using neural networks by Harmanani, H.

“…A sequential simulator was implemented for the proposed algorithm on a Linux Pentium PC under X Windows. Several circuits hare been attempted, all yielding sub-optimal solutions.…”
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Minimizing Mean Tardiness Subject To Unspecified Minimum Number Tardy For A Single Machine by Duffuaa, S. O.

“…It also uses an insertion algorithm which determines the optimal mean tardiness once the subset of tardy jobs is specified. …”
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One-Machine Scheduling To Minimize Mean Tardiness With Minimum Number Tardy by Duffuaa, S. O.

“…In this paper the one-machine scheduling problem with the objective of minimizing the mean tardiness subject to maintaining a prescribed number of tardy jobs is analysed An algorithm for solving this problem is presented. It is proved that the schedule generated by the proposed algorithm is indeed optimal.…”
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AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients by Azar, Danielle

“…Endocrinologists need to find a certain pattern in this data that would help them determine the optimal dosage of insulin to administer to each patient. …”
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One-Machine Scheduling To Minimize Mean Tardiness With Minimum Number Tardy by Duffuaa, S. O.

“…In this paper the one-machine scheduling problem with the objective of minimizing the mean tardiness subject to maintaining a prescribed number of tardy jobs is analysed An algorithm for solving this problem is presented. It is proved that the schedule generated by the proposed algorithm is indeed optimal.…”
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Determining Dominant Wind Directions by Selim, S.Z.

“…Important properties of the problem are discussed and a convergent solution algorithm is designed. The algorithm could yield local optimal solutions. …”
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