In this paper, we focus on evolution where diversity of species happens and stable coexistence of them is observed. We have built a simulation model. In our model, each individual loses energy by moving around, gains ...
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ISBN:
(纸本)9780889866171
In this paper, we focus on evolution where diversity of species happens and stable coexistence of them is observed. We have built a simulation model. In our model, each individual loses energy by moving around, gains energy by eating foods, and dies when it exhausts all the energy or lifespan is reached. The individual has three components (eyes, a mouth, and legs). Eyes and Legs have ability levels. As to the mouths, a few types are prepared, and we assume that each type of mouths can digest a specific kind of foods. The genes of the individual specify the ability levels of the eyes and the legs, and a type of the mouth each of which has different energy consumption. A number of individuals were put on the field, and were made to move for certain period, and the remaining energy was measured. Individuals join to multiplication in proportion to the remaining energy. As the result, evolution and the adaptation to the environments occured through generations, and more than one species coexisted in a certain environment. In the real world, many species coexist and hold stability under the environment where one highly adapted species seems to be dominant. This phenomenon has been observed in our simple model.
An important issue in large power markets is the optimization of total transmission capacity (TTC). This paper presents a genetic approach for the placement of one Thyristor controlled series capacitor (TCSC) in dereg...
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ISBN:
(纸本)9781921897078
An important issue in large power markets is the optimization of total transmission capacity (TTC). This paper presents a genetic approach for the placement of one Thyristor controlled series capacitor (TCSC) in deregulated power systems to increase TTC and improve the voltage stability. Detailed analysis is presented for multi-machine networks with multiple power-sellers and multiple power-buyers (power-consumer). Simulation results before and after compensation are used to analysis the impacts of TCSC on the IEEE 14-bus test system under deregulated conditions.
Orthopaedic implant materials are chosen considering their favourable mechanical properties and their compatibility to the human body. This study aims at proposing a suitable implant material for the hip joint, one of...
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ISBN:
(纸本)9789811387678;9789811387661
Orthopaedic implant materials are chosen considering their favourable mechanical properties and their compatibility to the human body. This study aims at proposing a suitable implant material for the hip joint, one of the most vital synovial joints of the human body. The current practice involves the use of Ultra-High-Molecular Weight Polyethylene (UHMWPE) for acetabular cup replacements in the hip joint. The debris produced from the use of such acetabular sockets may trigger adverse tissue reactions, which may account to osteolysis in the course of time. This study aims at developing new UHMWPE composites with various reinforcements to improve its structural integrity in vivo, and other related performance. This study employs Artificial Neural Network (ANN) and genetic algorithm (GA) for the above-said purpose. Numerous experimental data that involves the usage of UHMWPE reinforced with carbon nanotube (CNT) and Graphene are compiled to develop three distinct models for Young's modulus, tensile strength and hardness using ANN. The fundamental relation between the composition and particle sizes of two different reinforcement materials were explored using simulation studies for all three models. The best established ANN model from each mechanical property is considered as an objective function and for optimization using GA with different constraints on the composition of reinforcements in tandem to obtain the appropriate composition and the particle sizes of reinforcements corresponding to the respective mechanical properties that led to designing UHMWPE composites reinforced with multiple nanoparticles having improved performance for its application as orthopaedic implant material.
The most common death is due to the condition that affects the heart is Cardiovascular disease (CVD). The inadequate oxygen to the heart leads to the symptoms like fatigue and chest pain (angina). This paper proposes ...
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ISBN:
(纸本)9781538634769
The most common death is due to the condition that affects the heart is Cardiovascular disease (CVD). The inadequate oxygen to the heart leads to the symptoms like fatigue and chest pain (angina). This paper proposes a framework which incorporates the pre-processing step, Interval Vague set, Fuzzy Association Rule mining and Fuzzy Correlation rule mining for the decision making process. In this paper, the proposed framework mainly focused on the criteria that are causing the heart attack among the people. The pre-processing step is used to reduce the size of the heart disease dataset. Using the Rule Mining algorithm, the set of rules are generated for the prediction of heart diseases based on the selected criteria. Interval vague set is used to solve the decision making problem among the doctors regarding the heart disease among the patient who are in the hesitant state.
The presence of responsive loads in smart grids affects the power system problems such as distributed generations (DGs) studies. Newly, due to increased interest in low carbon energy supply, installation of renewable ...
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The presence of responsive loads in smart grids affects the power system problems such as distributed generations (DGs) studies. Newly, due to increased interest in low carbon energy supply, installation of renewable energy sources (RESs) appears to be a promising solution for generating clean and unlimited energy. The penetration of photovoltaics (PVs) in distribution networks would definitely affect the power system problems such as capacitor installation strategies. Hence, an optimal procedure is proposed herein which takes into account the simultaneous placement of PV-based DGs, smart meters (SMs), and capacitors in distribution networks taking into account different load curves, electricity prices, and hourly photovoltaic power generation in a daily basis. SMs are taken into consideration for the sake of successful implementation of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Moreover, the seasonal changes in daily load and renewable generations have been also modeled as an impressive factor in the founded methodology. The optimization procedure is handled with geneticalgorithm (GA) and tested on IEEE 69-bus radial distribution test system aiming at minimization of energy losses costs. Focusing on numerical studies, the distributed reactive support capability of PVs in altering the SM and capacitor placement solutions are discussed in depth to certify their substantial effects. The obtained results are encouraging.
For cluster-based target tracing in wireless sensor networks (WSN),tracking by only one cluster is not effective. Tracking tasks are collaborative,dynamic and distributed tasks and are executed in several *** order to...
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For cluster-based target tracing in wireless sensor networks (WSN),tracking by only one cluster is not effective. Tracking tasks are collaborative,dynamic and distributed tasks and are executed in several *** order to maintain a certain degree of service quality and a reasonable system lifetime,energy needs to be optimized at every stage of system *** node clustering is another very important optimization *** that are clustered together will easily be able to communicate with each other. Considering energy as an optimization parameter with multi-cluster WSN,the model of target tracking and the mode of energy consumption have been *** energy optimization,an optimal geneticalgorithm for task allocation among these gateways is studied which balance the energy consumption among concerning gateways. Experiments are designed and simulation results show that energy savings can be obtained with the proposed algorithm.
In this paper we propose a new feature extraction scheme for hyperspectral images based on mutual information. Relevance of extracted feature set to class label has been measured by average of mutual information betwe...
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ISBN:
(纸本)9781424467600
In this paper we propose a new feature extraction scheme for hyperspectral images based on mutual information. Relevance of extracted feature set to class label has been measured by average of mutual information between each of them and class label and Redundancy of them is measured by average of mutual information between each pair of them. Based on relevance of features and redundancy between them, we propose a cost function that maximize relevance of extracted features and simultaneously minimize redundancy between them. This cost function has been already used for feature selection. In this paper we will find the parameters of an optimal linear mapping by optimizing the proposed cost function with respect them. Linear methods are attractive due to their simplicity. Because of nonlinear and nonconvex relation between proposed cost function and the parameters, we use geneticalgorithm for optimization. Mutual information accounts for higher order statistics, not just for second order as PCA and LDA do. Hence mutual information is a better criterion for hyperspectral images because they have higher order statistics than two. Our classification results for AVARIS data shows proposed method has better performance over PCA and LDA.
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