Computer Sciences Commons^™

Marine Quay Crane Scheduling Using A Combined Modified Genetic Algorithm And Priority Rules Approach, V. H. Nguyen, D. T. Nguyen

Civil & Environmental Engineering Faculty Publications

Quay crane scheduling problem (QCSP) is the problem of the allocation of quay cranes to handle the unloading and loading of containers at seaport container terminals and defining the service sequence of vessel bays of each quay crane. The treatment of crane interference constraints and the increased in vessel size make the problem difficult to solve. Due to the growing interest in applied research for this problem, many researchers have used different algorithms and methods to obtain some solutions. This paper will propose a modified genetic algorithm combined with priority rules to deal with it. The advantage of the proposed …

Capso: A Multi-Objective Cultural Algorithm System To Predict Locations Of Ancient Sites, Samuel Dustin Stanley

Wayne State University Dissertations

ABSTRACT

CAPSO: A MULTI-OBJECTIVE CULTURAL ALGORITHM SYSTEM TO PREDICT LOCATIONS OF ANCIENT SITES

by

SAMUEL DUSTIN STANLEY

August 2019

Advisor: Dr. Robert Reynolds

Major: Computer Science

Degree: Doctor of Philosophy

The recent archaeological discovery by Dr. John O’Shea at University of Michigan of prehistoric caribou remains and Paleo-Indian structures underneath the Great Lakes has opened up an opportunity for Computer Scientists to develop dynamic systems modelling these ancient caribou routes and hunter-gatherer settlement systems as well as the prehistoric environments that they existed in. The Wayne State University Cultural Algorithm team has been interested assisting Dr. O’Shea’s archaeological team by …

Design And Fabrication Of A Dual-Polarized, Dual-Band Reflectarray Using Optimal Phase Distribution, Iman Aryanian, Arash Ahmadi, Mehdi Rabbani, Sina Hassibi, Majid Karimipour

Turkish Journal of Electrical Engineering and Computer Sciences

Two main factors limiting the reflectarray bandwidth are different phase slopes versus the frequency at every point on the aperture and the phase limitation of comprising elements at different frequencies. Considering these two factors, a novel design method is proposed to implement a dual-band, dual-polarized reflectarray antenna in X and Ku bands. An optimization algorithm is adopted to find the optimum phase for each unit cell on the reflectarray aperture. The best geometrical parameters of the phasing elements are suggested based on the phase variation of the element versus frequency and the element position with respect to the antenna feed. …

Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we describe histogram matching, a metric for measuring the distance of two datasets with exactly the same features, and embed it into a mixed integer programming formulation to partition a dataset into fixed size training and test subsets. The partition is done such that the pairwise distances between the dataset and the subsets are minimized with respect to histogram matching. We then conduct a numerical study using a well-known machine learning dataset. We demonstrate that the training set constructed with our approach provides feature distributions almost the same as the whole dataset, whereas training sets constructed via …

Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan

Turkish Journal of Electrical Engineering and Computer Sciences

The development and improvement of control techniques has attracted many researchers for many years. Especially in the controller design of complex and nonlinear systems, various methods have been proposed to determine the ideal control parameters. One of the most common and effective of these methods is determining the controller parameters with optimization algorithms.In this study, LQR controller design was implemented for position control of the double inverted pendulum system on a cart. First of all, the equations of motion of the inverted pendulum system were obtained by using Lagrange formulation. These equations were linearized by Taylor series expansion around the …

Evolutionary Approaches For Weight Optimization In Collaborative Filtering-Based Recommender Systems, Sevgi̇ Yi̇ği̇t Sert, Yilmaz Ar, Gazi̇ Erkan Bostanci

Turkish Journal of Electrical Engineering and Computer Sciences

Collaborative filtering is one of the widely adopted approaches in recommender systems used for e-commerce applications, stating that users having similar tastes will have similar preferences in the future. The literature presents a number of similarity metrics such as the extended Jaccard coefficient to quantify these preference similarities. This paper aims to improve prediction accuracy by optimizing the similarity values computed using these metrics by adopting two biologically inspired approaches, namely artificial bee colony and genetic algorithms, with a bottom-up approach, suggesting that any improvement on a single-user basis will reflect on the overall prediction accuracy. Detailed statistical analysis was …

A New Approach For Wind Turbine Placement Problem Using Modified Differential Evolution Algorithm, Hüseyi̇n Hakli

Turkish Journal of Electrical Engineering and Computer Sciences

Energy use is increasing worldwide with industrialization and advancing technology. Following this increase, renewable energy resources are increasingly preferred to reduce the costs of energy production. Wind energy is preferred as a renewable energy resource because it is clean and safe. Wind turbines are used to meet the demand for wind energy. They are placed close to each other to generate higher amounts of energy. However, the wake effect problem arises in these types of layouts, and this hinders the turbines from producing the desired yield. A modified differential evolution (MDE) algorithm was proposed in this study to solve the …

Design Of Virtual Interactive Simulations For Surgical Training, Doga Demirel

Theses and Dissertations

Design and development of a virtual reality based surgical simulation has many steps and the first and most important step is the comprehensive analysis of the surgery. We performed comprehensive analysis, hierarchical task analysis, which allowed steps and goals of the surgery to be understood while expressing the order of execution and hierarchical relations between the tasks of the surgery. Time and performance metrics derived from the comprehensive analysis provides detailed procedural feedback throughout the surgical simulation, which will help classify surgeon’s skill level. We developed quantitative performance metrics for arthroscopy-based rotator cuff surgery with the goal to establish objective …

A Parallelized Implementation Of Cut-And-Solve And A Streamlined Mixed-Integer Linear Programming Model For Finding Genetic Patterns Optimally Associated With Complex Diseases, Michael Yip-Hin Chan

Theses

With the advent of genetic sequencing, there was much hope of finding the inherited elements underlying complex diseases, such as late-onset Alzheimer’s disease (AD), but it has been a challenge to fully uncover the necessary information hidden in the data. A likely contributor to this failure is the fact that the pathogenesis of most complex diseases does not involve single markers working alone, but patterns of genetic markers interacting additively or epistatically. But as we move upwards beyond patterns of size two, it quickly becomes computationally infeasible to examine all combinations in the solution space. A common solution to solving …

Swarm Intelligence As An Optimization Technique, Alma Bregaj

International Journal of Business and Technology

Optimization techniques inspired by swarm intelligence have become increasingly popular during the last years. Swarm intelligence is based on nature-inspired behaviours and is successfully applied to optimisation problems in a variety of fields. The advantage of these approaches over traditional techniques is their robustness and flexibility. These properties make swarm intelligence a successful design paradigm for algorithms that deal with increasingly complex problems. In this paper I am focused on the comparison between different swarmbased optimisation algorithms and I have presented some examples of real practical applications of these algorithms.

Concept Of Online Assisted Platform For Technologies And Management In Communications – Optimek, Galia Marinova, Vassil Guliashki, Ognyan Chikov

International Journal of Business and Technology

The paper describes the concept of a Multimodular Multydisciplinary platform, contacting through unified templates in a Portal with knowledge, with Useful INTERNET resources, in order to provide advanced research and education. Usually the online resources available are mainly in the area of e- and distance education, but still an understanding is missing for the scale and the use of studying and the systematization of the online resource. The new concept has an accent of the useful INTERNET resource and the development of a System of nets to it, in the aim of solving tasks and generating new knowledge in the …

Simulation Based Optimisation Of Ground Crews: Case Of A Regional Airport, Blaz Rodic, Alenka Baggia

UBT International Conference

Paper presents the simulation models built within an airport ground crew scheduling automatization project at a regional airport. Our goal was to develop robust ground crew task scheduling and shift generation algorithms that would improve on existing heuristic rules. We have utilized simulation modeling to develop and validate the algorithms, starting with a model of the existing scheduling process coded and visualized in spreadsheet software and ending with a hybrid Discrete Event and Agent Based model used for the visualization and verification of the optimized processes. Explicit and tacit expert knowledge was recorded through meetings with airport personnel managers and …

Towards Parallel Quantum Computing: Standard Quantum Teleportation Algorithm Is, In Some Reasonable Sense, Unique, Oscar Galindo, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical problems, the computation speed of modern computers is not sufficient. Due to the fact that all speeds are bounded by the speed of light, the only way to speed up computations is to further decrease the size of the memory and processing cells that form a computational device. At the resulting size level, each cell will consist of a few atoms -- thus, we need to take quantum effects into account. For traditional computational devices, quantum effects are largely a distracting noise, but new quantum computing algorithms have been developed that use quantum effects to speed up …

Why Max And Average Poolings Are Optimal In Convolutional Neural Networks, Ahnaf Farhan, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we do not know the exact relation between different quantities; this relation needs to be determined based on the empirical data. This determination is not easy -- especially in the presence of different types of uncertainty. When the data comes in the form of time series and images, many efficient techniques for such determination use algorithms for training convolutional neural network. As part of this training, such networks "pool" several values corresponding to nearby temporal or spatial points into a single value. Empirically, the most efficient pooling algorithm consists of taking the maximum of the pooled …

Hyper-Optimized Machine Learning And Deep Learning Methods For Geo-Spatial And Temporal Function Estimation, Neelabh Pant

Computer Science and Engineering Dissertations - Archive

Owing to a high degree of freedom in human mobility, accurate modelling/estimation of human mobility function remains a challenge. Numerous work in the literature have tried to address the challenge using various traditional machine learning methods on spatio-temporal attributes of data. We compare the use of Varied-K Means clustering, Hidden Markov Model techniques, feed forward neural networks, recurrent neural networks (RNN) and Long Short Term Recurrent Neural Networks (LSTM) to predict a user's future movement based on the user's past historical data. Although several techniques were proposed to predict a user's movement, not many have concentrated on a user's location …

Optimization Under Fuzzy Constraints: From A Heuristic Algorithm To An Algorithm That Always Converges, Vladik Kreinovich, Juan Carlos Figueroa-Garcia

Departmental Technical Reports (CS)

An efficient iterative heuristic algorithm has been used to implement Bellman-Zadeh solution to the problem of optimization under fuzzy constraints. In this paper, we analyze this algorithm, explain why it works, show that there are cases when this algorithm does not converge, and propose a modification that always converges.

Multi-Stop Routing Optimization: A Genetic Algorithm Approach, Abbas Hommadi

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In this research, we investigate and propose new operators to improve Genetic Algorithm’s performance to solve the multi-stop routing problem. In a multi-stop route, a user starts at point x, visits all destinations exactly once, and then return to the same starting point. In this thesis, we are interested in two types of this problem. The first type is when the distance among destinations is fixed. In this case, it is called static traveling salesman problem. The second type is when the cost among destinations is affected by traffic congestion. Thus, the time among destinations changes during the day. In …

A Holistic Computational Approach To Boosting The Performance Of Protein Search Engines, Majdi Ahmad Mosa Maabreh

Dissertations

Despite availability of several proteins search engines, due to the increasing amounts of MS/MS data and database sizes, more efficient data analysis and reduction methods are important. Improving accuracy and performance of protein identification is a main goal in the community of proteomic research. In this research, a holistic solution for improvement in search performance is developed.

Most current search engines apply the SEQUEST style of searching protein databases to define MS/MS spectra. SEQUEST involves three main phases: (i) Indexing the protein databases, (ii) Matching and Ranking the MS/MS spectra and (iii) Filtering the matches and reporting the final proteins. …

Virtualization In Wireless Sensor Networks: Fault Tolerant Embedding For Internet Of Things, Omprakash Kaiwartya, Abdul Hanan Abdullah, Yue Cao, Jaime Lloret, Sushil Kumar, Rajiv Ratn Shah, Mukesh Prasad, Shiv Prakash

Research Collection School Of Computing and Information Systems

Recently, virtualization in wireless sensor networks (WSNs) has witnessed significant attention due to the growing service domain for IoT. Related literature on virtualization in WSNs explored resource optimization without considering communication failure in WSNs environments. The failure of a communication link in WSNs impacts many virtual networks running IoT services. In this context, this paper proposes a framework for optimizing fault tolerance in virtualization in WSNs, focusing on heterogeneous networks for service-oriented IoT applications. An optimization problem is formulated considering fault tolerance and communication delay as two conflicting objectives. An adapted non-dominated sorting based genetic algorithm (A-NSGA) is developed to …

Multigeneration Product Diffusion In The Presence Of Strategic Consumers, Zhiling Guo, Jianqing Chen

Research Collection School Of Computing and Information Systems

Frequent new product releases pose significant challenges for firms as they manage successive generations of product diffusion. We develop an analytical model to study the effect of different purchase options by strategic consumers on a firm's profit and the firm's strategies for the timing and pricing of its successive generations of product diffusion. We show that consumers' strategic behavior, although adversely affecting the sales of the first-generation product, positively influences the sales of the second-generation product through an initial “seeding” effect. The influence of strategic consumers on profit and sales depends largely on the discount-to-price ratio of the first generation …

Gradient Estimation For Attractor Networks, Thomas Flynn

Dissertations, Theses, and Capstone Projects

It has been hypothesized that neural network models with cyclic connectivity may be more powerful than their feed-forward counterparts. This thesis investigates this hypothesis in several ways. We study the gradient estimation and optimization procedures for several variants of these networks. We show how the convergence of the gradient estimation procedures are related to the properties of the networks. Then we consider how to tune the relative rates of gradient estimation and parameter adaptation to ensure successful optimization in these models. We also derive new gradient estimators for stochastic models. First, we port the forward sensitivity analysis method to the …

Integrated Strategies For Sustainable Wastewater-Based Algal Biofuel Production And Environmental Mitigation In The Us, Javad Roostaei

Wayne State University Dissertations

Integration of algae cultivation with wastewater treatment has received increasing interest as a cost-effective strategy for biofuel production. However, there has been no full assessment of algal biofuel production with wastewater on macro-scale by taking into account wastewater resources, land availability, CO2 emission resources, and geographic variation. This research addressed and evaluated the use of wastewater for algae cultivation, in terms of modeling and laboratory experiments. The first goal of this research was to develop a spatially explicit lifecycle model, by integrating life cycle assessment (LCA), and Geographic Information Systems (GIS) analysis, for the evaluation of the environmental and economic …

Choice Of Battery Energy Storage For A Hybrid Renewable Energy System, Kusum Lata Tharani, Ratna Dahiya

Turkish Journal of Electrical Engineering and Computer Sciences

There are certain unelectrified villages across the Indian subcontinent where providing supply through the grid is difficult due to forest cover or mountainous terrain. The most feasible option is to provide off-grid electrification through renewable energy resources such as solar or wind energy. These intermittent sources do not promise a 24 $\times $ 7 supply system. Thus, along with solar or wind energy systems, it becomes important to use a renewable resource, such as biomass, which is available in abundance in rural areas. The need for battery energy storage becomes mandatory in order to store the surplus energy produced by …

The Impact Of Transmission Power Levels Set Size On Lifetime Of Wireless Sensor Networks In Smart Grids, Hüseyi̇n Uğur Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor networks (WSNs) have been confirmed as one of the most promising technologies for many smart grid (SG) applications due to their low complexity and inexpensive costs. A typical WSN is formed with numerous battery limited sensor nodes mounted on critical components of a SG system for monitoring applications. Acquired monitoring data by sensor nodes are conveyed to the base station generally by using multihop communication techniques. WSN-based SG applications encounter severe propagation losses due to extreme channel conditions of the SG environment. In order to reduce possible packet errors caused by channel variations, transmission power control approaches can …

Damping Wide-Area Oscillations In Power Systems: A Model Predictive Controldesign, Emrah Biyik, Munir Husein

Turkish Journal of Electrical Engineering and Computer Sciences

Electromechanical oscillations in power systems have been observed ever since synchronous generators were interconnected to provide reliability and higher generation capacity, and they have become a severe threat for the safe and economic operation of modern interconnected power grids. To dampen these oscillations, wide-area damping controllers (WADCs) have been introduced by utilizing wide-area measurement systems and synchronized phasor measurement units. In this paper, we present a systematic approach for designing WADCs using a model predictive control (MPC) technique to damp interarea oscillations in the power system. The MPC controller computes optimal control signals for the excitation system of a remote …

An Elitist Approach For Solving The Traveling Salesman Problem Using An Animalmigration Optimization Algorithm, Ezgi̇ Ülker

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents an improved version of the animal migration optimization (AMO) algorithm for solving the traveling salesman problem (TSP), which is classified as a combinatorial NP-hard problem. AMO is one of the recent metaheuristic algorithms inspired by the migration behavior of animals and has been efficiently applied to a variety of optimization problems. The algorithm is improved by reconstructing the neighborhood topology of each animal during the migration. This modified algorithm is called the elitist animal migration optimization (ELAMO) algorithm, since elitism is introduced as a way in which the positions of the leaders are considered for the neighborhood …

Ionolab-Map: An Automatic Spatial Interpolation Algorithm For Total Electron Content, Muhammet Necat Devi̇ren, Feza Arikan

Turkish Journal of Electrical Engineering and Computer Sciences

Investigation of the variability of total electron content (TEC) is one of the most important parameters of the observation and monitoring of space weather, which is the main cause of signal disturbance in space-based communication, positioning, and navigation systems. TEC is defined as the total number of electrons on a ray path. The Global Positioning System (GPS) provides a cost-effective solution for the estimation of TEC. Due to various physical and operational disturbances, TEC may have temporal and spatial domain gaps. Global ionospheric maps (GIMs) provide worldwide TEC with 1- to 2-h temporal resolution and $2.5^{\circ}\, \times 5^{\circ}$ spatial resolution …

Application Of Domination Integrity Of Graphs In Pmu Placement In Electric Power Networks, Mariappan Saravanan, Ramalingam Sujatha, Raman Sundareswaran, Muthu Selvan Balasubramanian

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose the application of the concept of power domination integrity to an electric power network. A phasor measurement unit (PMU) is used to analyze and control the power system by measuring voltage phase in electrical nodes and transmission lines. Due to the high cost of PMUs, it is necessary to minimize the number of PMUs such that the depth of observability is ensured. Placing PMUs in a network can be formulated as a graph theoretic problem of finding the minimum number of nodes (PMUs) in a graph that has a maximum number of links with other …

How To Best Apply Neural Networks In Geosciences: Towards Optimal "Averaging" In Dropout Training, Afshin Gholamy, Justin Parra, Vladik Kreinovich, Olac Fuentes, Elizabeth Y. Anthony

Departmental Technical Reports (CS)

The main objectives of geosciences is to find the current state of the Earth -- i.e., solve the corresponding inverse problems -- and to use this knowledge for predicting the future events, such as earthquakes and volcanic eruptions. In both inverse and prediction problems, often, machine learning techniques are very efficient, and at present, the most efficient machine learning technique is deep neural training. To speed up this training, the current learning algorithms use dropout techniques: they train several sub-networks on different portions of data, and then "average" the results. A natural idea is to use arithmetic mean for this …

A Selective-Discrete Particle Swarm Optimization Algorithm For Solving A Class Of Orienteering Problems, Aldy Gunawan, Vincent F. Yu, Perwira Redi, Parida Jewpanya, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This study addresses a class of NP-hard problem called the Orienteering Problem (OP), which belongs to a well-known class of vehicle routing problems. In the OP, a set of nodes that associated with a location and a score is given. The time required to travel between each pair of nodes is known in advance. The total travel time is limited by a predetermined time budget. The objective is to select a subset of nodes to be visited that maximizes the total collected score within a path. The Team OP (TOP) is an extension of OP that incorporates multiple paths. Another …