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Design of low power multiplierless FIR filter with enhanced adder efficiency using flower pollination optimization

APPLIED ACOUSTICS 2021年 174卷 107792-107792页

作者： Kumar, A. Sharma, I Balyan, L. K. PDPM Indian Inst Informat Technol Design & Mfg Ja Jabalpur Madhya Pradesh India Malaviya Natl Inst Technol Jaipur Rajasthan India

This paper presents an improved design of minimal power multiplierless finite impulse response (FIR) by using flower pollination algorithm (FPA) and newly proposed hybrid common sub-expression elimination (CSE) algorithm. The novel extract of this paper is three fold: first, enhancement of the power performance by reducing the switching activity;second, raising adder efficiency using newly proposed hybrid CSE algorithm;and third, optimizing the frequency response characteristics of filter by controlling ripples in passband and stopband region using FPA in one step. For this purpose, the minima of an objective function is achieved, constructed as sum of integral mean squared error with allowable tolerable limits to control ripples in passband and stopband region, and the dynamic power that has computed through hamming distance (HD) between two successive filter coefficients. In addition to this, the application of recently proposed CSE reduces the amount of adders, and lowers the value of HD. The significance of proposed algorithm is measured on the basis of different performance evaluation parameter such as;stopband attenuation (A(s)), stopband ripple (delta(s)), passband ripple (delta(p)), hamming distance (HD), power and amount of adders respectively. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Finite impulse response (FIR) filter Flower pollination algorithm (FPA) Dynamic power Hamming distance (HD) optimization algorithms Common sub-expression elimination algorithms (CSE)

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Explainable data-driven optimization for complex systems with non-preferential multiple outputs using belief rule base

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APPLIED SOFT COMPUTING 2021年 110卷 107581-107581页

作者： Chang, Leilei Zhang, Limao Hangzhou Dianzi Univ Dept Automat Hangzhou Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn Singapore Singapore

To better handle problems with non-preferential multi-outputs (NPMO), a new approach is proposed in this study by employing the belief rule base (BRB) to provide a superior nonlinearity modeling ability as well as good explainability. The new approach is thus called NPMO-BRB. First, a new optimization model is constructed where the optimization objective is the integration of multi-outputs and respective constraints are designed. Then, a new optimization algorithm with a new customized gene makeup is designed where the NPMO-BRB inferencing process is embedded in the fitness calculation procedure. A practical case study on Changsha Metro Line 4 is studied to use multiple geological parameters to infer multiple operational parameters. Case study results show that NPMO-BRB has shown superior performance in comparison with the random forest (RF), the backpropagation neural network (BPNN), the Gradient Gaussian Process (GPR), as well as multiple separate BRBs. Owing to the explainability provided by the NPMO-BRB approach, further investigations into the belief distribution comparison reveal more information that can be used as practical work guidelines. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Belief rule base (BRB) Non-preferential multi-output (NPMO) optimization algorithms

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NONLINEAR VIBRATIONS OF BEAMS WITH BILINEAR HYSTERESIS AT SUPPORTS: INTERPRETATION OF EXPERIMENTAL RESULTS

NONLINEAR VIBRATIONS OF BEAMS WITH BILINEAR HYSTERESIS AT SU...

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ASME International Mechanical Engineering Congress and Exposition (IMECE)

作者： Balasubramanian, Prabakaran Franchini, Giulio Ferrari, Giovanni Painter, Brian Karazis, Kostas Amabili, Marco McGill Univ Dept Mech Engn Montreal PQ Canada Framatome Inc Lynchburg VA USA Univ Parma Dipartimento Ingn & Architettura Parma PR Italy

ISBN: (纸本)9780791885611

Several structures of important industrial relevance feature large-amplitude vibration, which can have an initially hardening or a softening behavior. Models with quadratic and cubic nonlinear stiffness terms are often used to predict the nonlinear dynamics of such structures. If boundary conditions constitute an important cause of nonlinearity, however, it may not be possible to describe the nonlinear behavior of these systems by means of these nonlinear terms. The bundles of fuel rods immersed in the coolant flow of pressurized water reactors constitute an important example of extreme softening behavior, which is not described accurately by the simple adoption of nonlinear stiffness terms proportional to the square and to the cube of displacement in the equation of motion. In fact, the spacer grids, which support the nuclear fuel rods inside the reactors, constitute nonlinear boundary conditions, and are responsible of the peculiar softening behavior. Dedicated experiments on the rotational constraint applied by the spacer grids were performed, revealing a softening stiffness, which conforms extremely well with a bilinear model with hysteresis, such as the one formulated by Caughey. Therefore, a single degree-of-freedom equation with bilinear stiffness terms was employed to model the large-amplitude vibrations of single and bundled fuel rods immersed in quiescent water, which were detailed by previous stepped-sine experiments. A viscous dissipative term was initially retained for modelling damping, since several sources of dissipation are present for fuel rods immersed in water, besides hysteresis at the spacer grid supports. A satisfying fit of the experimental frequency- and time-domain curves was achieved through the use of an optimization algorithm for the tuning of stiffness and damping terms. Viscous damping, however, is not constant during large-amplitude vibrations, but is amplitude-dependent. Therefore, the value of the relevant parameter had to be change

关键词： Vibration Stiffness Damping Fuel rods Boundary-value problems Switches Water Equations of motion Fluids Coolants Hardening Energy dissipation Degrees of freedom Modeling Nonlinear dynamics Pressurized water reactors Displacement optimization algorithms Rods Flow (Dynamics)

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A Review of Existing Multi-Motor Electric Powertrain Sizing Strategies 24

A Review of Existing Multi-Motor Electric Powertrain Sizing ...

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24th International Conference on Electrical Machines and Systems (ICEMS)

作者： Castro, Marco Veliz Mukundan, Shruthi Filho, Claudio Lopes Byczynski, Glenn Minaker, Bruce Tjong, Jimi Kar, Narayan C. Univ Windsor Windsor ON N9B 3P4 Canada Nemak USA CAN 2 Towne Sq 300 Southfield MI 48076 USA

ISBN: (纸本)9788986510218

Multi-Motor Electric Vehicles (MMEVs) have been identified as a solution to the current disadvantages of Single Motor Electric Vehicles (EVs) in energy consumption and driving range. These improvements are achieved by operating each motor in its peak efficiency region, as appropriate for the driving scenario. Although MMEVs have increased efficiency, the extent is highly dependent on the sizes of the motors. Thus, some researchers have begun to determine the optimal motor sizes. This paper reviews existing literature on motor sizing techniques and analyzes their performance through overall powertrain dynamic and efficiency performance.

关键词： Motor sizing multi-motor electric vehicles optimization algorithms vehicle dynamics modelling

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EFFICIENT COMPUTATION OF SPARSE AND ROBUST MAXIMUM ASSOCIATION ESTIMATORS

arXiv

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arXiv 2023年

作者： Pfeiffer, Pia Alfons, Andreas Filzmoser, Peter Institute of Statistics and Mathematical Methods in Economics TU Wien Austria Department of Econometrics Erasmus Universiteit Rotterdam Netherlands

Robust statistical estimators offer resilience against outliers but are often computationally challenging, particularly in high-dimensional sparse settings. Modern optimization techniques are utilized for robust sparse association estimators without imposing constraints on the covariance structure. The approach splits the problem into a robust estimation phase, followed by optimization of a decoupled, biconvex problem to derive the sparse canonical vectors. An augmented Lagrangian algorithm, combined with a modified adaptive gradient descent method, induces sparsity through simultaneous updates of both canonical vectors. Results demonstrate improved precision over existing methods, with high-dimensional empirical examples illustrating the effectiveness of this approach. The methodology can also be extended to other robust sparse estimators. © 2023, CC BY.

关键词： optimization algorithms

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A goal-based weighting for composite indicators constructed through Ordered Weighted Averaging (OWA) operator

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METHODSX 2024年 12卷 102575页

作者： Liborio, Matheus Pereira Ekel, Petr Iakovlevitch Laudares, Sandro Martins, Carlos Augusto Paiva da Silva Pantifical Catholic Univ Minas Gerais 500 Dom Jose Gaspar St BR-30535901 Belo Horizonte MG Brazil

The Ordered Weighted Averaging (OWA) operator is a multicriteria method that has conquered space among researchers in the composite indicators field. Typically, OWA operator weights are defined by the decision maker. This type of weighting is highly criticized, as decision-makers are susceptible to errors and bias in judgment. Some methods have been used to define OWA operator weights objectively. However, none of them is concerned about the quality of the composite indicator. This paper introduces a method that defines the weights of the OWA operator based on two quality parameters of the composite indicator: the ability to capture the concept of the multidimensional phenomenon and the informational loss. The method can be implemented in Microsoft Excel Solver and has a high degree of flexibility and applicability in problems of a multidimensional nature and a high degree of appropriation by researchers and practitioners in the area. center dot Defines weights that maximize the ability of the composite indicator to capture the concept of the multidimensional phenomenon. center dot Considers restrictions to limit the informational loss of the composite indicator or emphasize positive or negative aspects of the multidimensional phenomenon. center dot Offers flexibility in setting the objective and constraints of the optimization algorithm.

关键词： Multicriteria methods Operation research Multidimensional problems Data-driven weighting scheme Informational loss optimization algorithms

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A SAFETY-SPACE-BASED APPROACH TO INSPECTION PATH PLANNING FOR THE SHEET METAL ASSEMBLIES

A SAFETY-SPACE-BASED APPROACH TO INSPECTION PATH PLANNING FO...

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ASME International Mechanical Engineering Congress and Exposition (IMECE)

作者： Liu, Yinhua An, Chao Duan, Zhenxia Univ Shanghai Sci & Technol Shanghai Peoples R China

ISBN: (纸本)9780791885567

The inspection path planning of sheet metal assemblies plays an important role in the measurement efficiency of large free-form surfaces. In the path generation of a 5-axis coordinate measurement machine (CMM), large calculation of collision detection and obstacle avoidance are needed in the traditional computer-aided inspection planning methods. Owing to structure complexity of large free-form surfaces, the planning procedures for collision detection and automatic collision-free trajectory generation is time-consuming and low-efficiency. To address this problem, a safety-space-based modeling approach is proposed to generate a feasible collision-free path for a large number of key measurement points. At first, based on the decomposition of the dynamic motion trajectory of the probe and discretizing of the inspected object, a continuous envelope space, i.e., safety space is constructed for candidate path generation of the probe. In the proposed planning strategy, the work of collision detection and avoidance are eliminated. Then, a heuristic optimization algorithm is used to generate the feasible trajectory in the constructed safety space for all the measurement points. At last, an inspection path planning case of a car door assembly was used to illustrate the procedure of the proposed method.

关键词： Inspection Safety Sheet metal Path planning Collisions (Physics) Trajectories (Physics) Probes Modeling optimization algorithms Coordinate measuring machines Machinery Doors Manufacturing Computer-aided engineering

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Multi-Objective Information Retrieval-Based NSGA-II optimization for Requirements Traceability Recovery

Multi-Objective Information Retrieval-Based NSGA-II Optimiza...

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IEEE International Conference on Electro Information Technology (EIT)

作者： Rodriguez, Danissa, V Carver, Doris L. Louisiana State Univ Div Comp Sci & Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9781728153179

The recovery of requirements traceability links assists multiple software development activities, including analyzing impact of changes, validating requirements, maintenance and evolution of software. Poor communication and time pressure problems often have resulted in organizations being unsuccessful in implementing traceability practices. A number of solutions for automatic recovery of links across software artifacts have been developed, including the application of textual analysis and information retrieval techniques. Link recovery with information retrieval has seen some success, but there is a need for methods that further enable the automatic generation of links. We investigate the requirements traceability recovery problem as an optimization problem;we study it as a multi-objective search in which we assign one-to-many relationships between each requirement to a code element by considering the semantic similarity between the textual content of requirements and the source code. We adapt the Non-dominated Sorting Genetic Algorithm, NSGA-II, to seek the optimal solution between two objective functions based on textual similarity using the similarity measures of Jaccard similarity and term frequency (TF-idf) combined with cosine similarity. Our IR-based NSGA-II returned values on average above 75% for both precision and recall for the recovered links. High precision and recall are positive results for our approach to requirements traceability recovery.

关键词： Requirements traceability link recovery optimization algorithms genetic algorithms NSGA-II

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Comparative Analysis of Heuristic-based Energy Efficient Protocol for M2M Communications in Green IoT

Comparative Analysis of Heuristic-based Energy Efficient Pro...

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3rd IEEE International Conference on Emerging Smart Computing and Informatics (IEEE-ESCI)

作者： Tupe, Umakant L. Kadam, Sonali Mahalle, Parikshit N. Marathwada Mitramandals Inst Technol Dept Comp Engn Pune Maharashtra India Bharati Vidyapiths Coll Engn Women Pune Maharashtra India SKNCOE Dept Comp Engn Pune Maharashtra India

ISBN: (纸本)9781728185194

There is a huge development in the Internet of Things (IoT) that causes massive deployment of sensors and thus automatic reconfigurable energy-efficient protocol for Green IoT is required. Machine-to-Machine (M2M) interactions are one of the core features of IoT. The M2M means the exchange of data among two or more entities, objects or machines, which do not require human interaction. To tackle the sustainability constraints of present IoT models, few developing models are thought to have been promised with new models. However, the fully usage of these models from communication, computing, and data processing for enhancing the energy efficiency of IoT still faces several basic defects. This paper tactics to plan for the comparative analysis on diverse heuristic approaches incorporated with Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol for energy-efficient M2M communication in Green IoT. The minimization of energy consumption by nodes in Green IoT is the main objective of the model. The algorithms like Genetic Algorithm (GA), Particle Swarm optimization (PSO), Artificial Bee Colony (ABC), Dargonfly Algorithm (DA), and Deer Hunting optimization Algorithm (DHOA) is adopted making the comparison part in energy-efficient Green IoT. This energy-efficient model maximizes the network lifetime finally.

关键词： Energy Efficient Protocol M2M Communications Green IoT Low Energy Adaptive Clustering Hierarchy optimization algorithms

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Online Spark Timing optimization With Complex High-Fidelity Combustion Phasing, Knock, and Coefficient of Variation of IMEP Models

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JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME 2021年第6期143卷 061007页

作者： Zhu, Qilun Prucka, Robert Wang, Shu Prucka, Michael Clemson Univ Automot Engn Dept Greenville SC 29607 USA FCA US LLC Auburn Hills MI 48326 USA

The combustion phasing of spark ignition (SI) engines is traditionally regulated with map-based spark timing (SPKT) control. The calibration of these maps is time-consuming for SI engines with a high number of control actuators. This paper proposes three online SPKT optimization algorithms that can utilize control-oriented semiphysics-based combustion models making the SPKT control algorithm more adaptive to different engine designs. These three SPKT optimizers do not require model inversion and derivative information. These methods also preserve the dependence between combustion phasing, knock, and coefficient of variation (COV) of indicated mean effective pressure (IMEP) models to avoid evaluating combustion models multiple times within one iteration. The two-phase and constraint relaxation methods are derived from direct search optimization theories. The recursive least square (RLS) polynomial fitting method can be considered as a virtual extreme seeking (ES) process that converts the original "black" box nonlinear constrained optimization into the solution of three low-order polynomial equations. Although these three online SPKT optimization approaches have unique properties making them preferable with certain types of combustion models, simulation and test results show that all of them can find the optimal SPKT with less than 10 evaluations of the combustion models. This fact makes it possible to implement the proposed model-based SPKT control strategy in future engine control units (ECUs).

关键词： Polynomials optimization Fittings Relaxation (Physics) Combustion optimization algorithms algorithms Engines

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