Bee Parameter Determination via Weighted Centriod Modified Simplex and Constrained Response Surface Optimisation Methods

Various intelligences and inspirations have been adopted into the iterative searching process called as meta-heuristics. They intelligently perform the exploration and exploitation in the solution domain space aiming to efficiently seek near optimal solutions. In this work, the bee algorithm, inspired by the natural foraging behaviour of honey bees, was adapted to find the near optimal solutions of the transportation management system, dynamic multi-zone dispatching. This problem prepares for an uncertainty and changing customers- demand. In striving to remain competitive, transportation system should therefore be flexible in order to cope with the changes of customers- demand in terms of in-bound and outbound goods and technological innovations. To remain higher service level but lower cost management via the minimal imbalance scenario, the rearrangement penalty of the area, in each zone, including time periods are also included. However, the performance of the algorithm depends on the appropriate parameters- setting and need to be determined and analysed before its implementation. BEE parameters are determined through the linear constrained response surface optimisation or LCRSOM and weighted centroid modified simplex methods or WCMSM. Experimental results were analysed in terms of best solutions found so far, mean and standard deviation on the imbalance values including the convergence of the solutions obtained. It was found that the results obtained from the LCRSOM were better than those using the WCMSM. However, the average execution time of experimental run using the LCRSOM was longer than those using the WCMSM. Finally a recommendation of proper level settings of BEE parameters for some selected problem sizes is given as a guideline for future applications.

Solving the Economic Dispatch Problem by Using Differential Evolution

This paper proposes an application of the differential evolution (DE) algorithm for solving the economic dispatch problem (ED). Furthermore, the regenerating population procedure added to the conventional DE in order to improve escaping the local minimum solution. To test performance of DE algorithm, three thermal generating units with valve-point loading effects is used for testing. Moreover, investigating the DE parameters is presented. The simulation results show that the DE algorithm, which had been adjusted parameters, is better convergent time than other optimization methods.

A Microstrip Antenna Design and Performance Analysis for RFID High Bit Rate Applications

Lately, an interest has grown greatly in the usages of RFID in an un-presidential applications. It is shown in the adaptation of major software companies such as Microsoft, IBM, and Oracle the RFID capabilities in their major software products. For example Microsoft SharePoints 2010 workflow is now fully compatible with RFID platform. In addition, Microsoft BizTalk server is also capable of all RFID sensors data acquisition. This will lead to applications that required high bit rate, long range and a multimedia content in nature. Higher frequencies of operation have been designated for RFID tags, among them are the 2.45 and 5.8 GHz. The higher the frequency means higher range, and higher bit rate, but the drawback is the greater cost. In this paper we present a single layer, low profile patch antenna operates at 5.8 GHz with pure resistive input impedance of 50 and close to directive radiation. Also, we propose a modification to the design in order to improve the operation band width from 8.7 to 13.8

Self-Adaptive Differential Evolution Based Power Economic Dispatch of Generators with Valve-Point Effects and Multiple Fuel Options

This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evolutionary algorithm for global optimization in many real problems. In this paper the key parameters of control in DE algorithm such as the crossover constant CR and weight applied to random differential F are self-adapted. The PED problem formulation takes into consideration of nonsmooth fuel cost function due to valve point effects and multi fuel options of generator. The proposed approach has been examined and tested with the numerical results of PED problems with thirteen-generation units including valve-point effects, ten-generation units with multiple fuel options neglecting valve-point effects and ten-generation units including valve-point effects and multiple fuel options. The test results are promising and show the effectiveness of proposed approach for solving PED problems.

Fuzzy Logic Based Determination of Battery Charging Efficiency Applied to Hybrid Power System

Battery storage system is emerging as an essential component of hybrid power system based on renewable energy resources such as solar and wind in order to make these sources dispatchable. Accurate modeling of battery storage system is ssential in order to ensure optimal planning of hybrid power systems incorporating battery storage. Majority of the system planning studies involving battery storage assume battery charging efficiency to be constant. However a strong correlation exists between battery charging efficiency and battery state of charge. In this work a Fuzzy logic based model has been presented for determining battery charging efficiency relative to a particular SOC. In order to demonstrate the efficacy of proposed approach, reliability evaluation studies are carried out for a hypothetical autonomous hybrid power system located in Jaisalmer, Rajasthan, India. The impact of considering battery charging efficiency as a function of state of charge is compared against the assumption of fixed battery charging efficiency for three different configurations comprising of wind-storage, solar-storage and wind-solar-storage.

Solving the Economic Dispatch Problem using Novel Particle Swarm Optimization

This paper proposes an improved approach based on conventional particle swarm optimization (PSO) for solving an economic dispatch(ED) problem with considering the generator constraints. The mutation operators of the differential evolution (DE) are used for improving diversity exploration of PSO, which called particle swarm optimization with mutation operators (PSOM). The mutation operators are activated if velocity values of PSO nearly to zero or violated from the boundaries. Four scenarios of mutation operators are implemented for PSOM. The simulation results of all scenarios of the PSOM outperform over the PSO and other existing approaches which appeared in literatures.

Growth and Mineral Content of Mokara chark kuan Pink Orchid as Affected by Allelopathic Lantana camara Weed

Growth and mineral nutrient elemental content were studied in Mokara chark kuan pink terrestrial orchid and wild Lantana camara weed agroecosystem. The treated subplots were encircled with L. camara plants and sprayed weekly with L. camara 10% leaf aqueous extract. Allelopathic interactions were possible through extensive invading root of L. camara plants into the treated orchid subplots and weekly L. camara leaf aqueous extract sprayings. Orchid growth was not significantly different in between the control and treated plots, but chlorosis and yellowish patches of leaves were observed in control orchid leaves. Nitrogen content in L. camara leaf was significantly higher than in orchid leaf, the order of importance of mineral nutrient contents in L. camara leaf was K>Mg>Na>N. In treated orchid leaf, the order of importance was N>K>Mg>Na. Orchid leaf N content from the treated plot was higher than control, but Mg and Na contents were almost similar.

Hybrid Optimization of Emission and Economic Dispatch by the Sigmoid Decreasing Inertia Weight Particle Swarm Optimization

This paper present an efficient and reliable technique of optimization which combined fuel cost economic optimization and emission dispatch using the Sigmoid Decreasing Inertia Weight Particle Swarm Optimization algorithm (PSO) to reduce the cost of fuel and pollutants resulting from fuel combustion by keeping the output of generators, bus voltages, shunt capacitors and transformer tap settings within the security boundary. The performance of the proposed algorithm has been demonstrated on IEEE 30-bus system with six generating units. The results clearly show that the proposed algorithm gives better and faster speed convergence then linearly decreasing inertia weight.

Emission Constrained Economic Dispatch for Hydrothermal Coordination

This paper presents an efficient emission constrained economic dispatch algorithm that deals with nonlinear cost function and constraints. It is then incorporated into the dynamic programming based hydrothermal coordination program. The program has been tested on a practical utility system having 32 thermal and 12 hydro generating units. Test results show that a slight increase in production cost causes a substantial reduction in emission.

Active Fiber Composites for Smart Damping of Doubly Curved Laminated Shells

This paper deals with the analysis of active constrained layer damping (ACLD) of doubly curved laminated composite shells using active fiber composite (AFC) materials. The constraining layer of the ACLD treatment has been considered to be made of the AFC materials. A three dimensional energy based finite element model of the smart doubly curved laminated composite shell integrated with a patch of such ACLD treatment has been developed to demonstrate the performance of the patch on enhancing the damping characteristics of the doubly curved laminated composite shells. Particular emphasis has been placed on studying the effect of variation of piezoelectric fiber orientation angle in the constraining AFC layer on the control authority of the ACLD patch.

Assessing Habitat-Suitability Models with a Virtual Species at Khao Nan National Park, Thailand

This study examined a habitat-suitability assessment method namely the Ecological Niche Factor Analysis (ENFA). A virtual species was created and then dispatched in a geographic information system model of a real landscape in three historic scenarios: (1) spreading, (2) equilibrium, and (3) overabundance. In each scenario, the virtual species was sampled and these simulated data sets were used as inputs for the ENFA to reconstruct the habitat suitability model. The 'equilibrium' scenario gives the highest quantity and quality among three scenarios. ENFA was sensitive to the distribution scenarios but not sensitive to sample sizes. The use of a virtual species proved to be a very efficient method, allowing one to fully control the quality of the input data as well as to accurately evaluate the predictive power of the analyses.

Multiclass Support Vector Machines for Environmental Sounds Classification Using log-Gabor Filters

In this paper we propose a robust environmental sound classification approach, based on spectrograms features driven from log-Gabor filters. This approach includes two methods. In the first methods, the spectrograms are passed through an appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criteria. The second method uses the same steps but applied only to three patches extracted from each spectrogram. To investigate the accuracy of the proposed methods, we conduct experiments using a large database containing 10 environmental sound classes. The classification results based on Multiclass Support Vector Machines show that the second method is the most efficient with an average classification accuracy of 89.62 %.

Fuzzy C-Means Clustering Algorithm for Voltage Stability in Large Power Systems

The steady-state operation of maintaining voltage stability is done by switching various controllers scattered all over the power network. When a contingency occurs, whether forced or unforced, the dispatcher is to alleviate the problem in a minimum time, cost, and effort. Persistent problem may lead to blackout. The dispatcher is to have the appropriate switching of controllers in terms of type, location, and size to remove the contingency and maintain voltage stability. Wrong switching may worsen the problem and that may lead to blackout. This work proposed and used a Fuzzy CMeans Clustering (FCMC) to assist the dispatcher in the decision making. The FCMC is used in the static voltage stability to map instantaneously a contingency to a set of controllers where the types, locations, and amount of switching are induced.

Power System Contingency Analysis Using Multiagent Systems

The demand of the energy management systems (EMS) set forth by modern power systems requires fast energy management systems. Contingency analysis is among the functions in EMS which is time consuming. In order to handle this limitation, this paper introduces agent based technology in the contingency analysis. The main function of agents is to speed up the performance. Negotiations process in decision making is explained and the issue set forth is the minimization of the operating costs. The IEEE 14 bus system and its line outage have been used in the research and simulation results are presented.

Power System Security Constrained Economic Dispatch Using Real Coded Quantum Inspired Evolution Algorithm

This paper presents a new optimization technique based on quantum computing principles to solve a security constrained power system economic dispatch problem (SCED). The proposed technique is a population-based algorithm, which uses some quantum computing elements in coding and evolving groups of potential solutions to reach the optimum following a partially directed random approach. The SCED problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Real Coded Quantum-Inspired Evolution Algorithm (RQIEA) is then applied to solve the constrained optimization formulation. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that RQIEA is very applicable for solving security constrained power system economic dispatch problem (SCED).

Integrating Hedgerow into Town Planning: A Framework for Sustainable Residential Development

The vast rural landscape in the southern United States is conspicuously characterized by the hedgerow trees or groves. The patchwork landscape of fields surrounded by high hedgerows is a traditional and familiar feature of the American countryside. Hedgerows are in effect linear strips of trees, groves, or woodlands, which are often critical habitats for wildlife and important for the visual quality of the landscape. As landscape interfaces, hedgerows define the spaces in the landscape, give the landscape life and meaning, and enrich ecologies and cultural heritages of the American countryside. Although hedgerows were originally intended as fences and to mark property and townland boundaries, they are not merely the natural or man-made additions to the landscape--they have gradually become “naturalized" into the landscape, deeply rooted in the rural culture, and now formed an important component of the southern American rural environment. However, due to the ever expanding real estate industry and high demand for new residential development, substantial areas of authentic hedgerow landscape in the southern United States are being urbanized. Using Hudson Farm as an example, this study illustrated guidelines of how hedgerows can be integrated into town planning as green infrastructure and landscape interface to innovate and direct sustainable land use, and suggest ways in which such vernacular landscapes can be preserved and integrated into new development without losing their contextual inspiration.

Application of Pattern Search Method to Power System Security Constrained Economic Dispatch

Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).

An Experimental Study on the Tensile Behavior of the Cracked Aluminum Plates Repaired with FML Composite Patches

Repairing of the cracks by fiber metal laminates (FMLs) was first done by some aeronautical laboratories in early 1970s. In this study, experimental investigations were done on the effect of repairing the center-cracked aluminum plates using the FML patches. The repairing processes were conducted to characterize the response of the repaired structures to tensile tests. The composite patches were made of one aluminum layer and two woven glassepoxy composite layers. Three different crack lengths in three crack angles and different patch lay-ups were examined. It was observed for the lengthen cracks, the effect of increasing the crack angle on ultimate tensile load in the structure was increase. It was indicated that the situation of metal layer in the FML patches had an important effect on the tensile response of the tested specimens. It was found when the aluminum layer is farther, the ultimate tensile load has the highest amount.

Texture Based Weed Detection Using Multi Resolution Combined Statistical and Spatial Frequency (MRCSF)

Texture classification is a trendy and a catchy technology in the field of texture analysis. Textures, the repeated patterns, have different frequency components along different orientations. Our work is based on Texture Classification and its applications. It finds its applications in various fields like Medical Image Classification, Computer Vision, Remote Sensing, Agricultural Field, and Textile Industry. Weed control has a major effect on agriculture. A large amount of herbicide has been used for controlling weeds in agriculture fields, lawns, golf courses, sport fields, etc. Random spraying of herbicides does not meet the exact requirement of the field. Certain areas in field have more weed patches than estimated. So, we need a visual system that can discriminate weeds from the field image which will reduce or even eliminate the amount of herbicide used. This would allow farmers to not use any herbicides or only apply them where they are needed. A machine vision precision automated weed control system could reduce the usage of chemicals in crop fields. In this paper, an intelligent system for automatic weeding strategy Multi Resolution Combined Statistical & spatial Frequency is used to discriminate the weeds from the crops and to classify them as narrow, little and broad weeds.

Development of Low-Profile Antenna for Mini UAV with Reconnaissance Mission

Microstrip antennas are conformable to planar and nonplanar surfaces, simple and inexpensive to fabricate using modern printed-circuit technology. Circular polarization of low-profile microstrip patch with high bandwidth is achieved in this research through the use of a three-cross-arms branch-line coupler with sequential rotated arrays, another low-profile antenna of hollow cylinder is also proposed and the function of reconnaissance with microstrip antenna on Mini UAV (unmanned aerial vehicle) are evaluated in practical flight test.