With the advent of the smart grid, it has become possible to improve the energy systems. To optimize the energy consumption pattern of the appliances, home energy management system is proposed for smart homes. Energy ...
详细信息
ISBN:
(纸本)9783319936598;9783319936581
With the advent of the smart grid, it has become possible to improve the energy systems. To optimize the energy consumption pattern of the appliances, home energy management system is proposed for smart homes. Energy management in smart homes is a challenging task, therefore, the concept of demand-side management was introduced. For the effective scheduling of smart appliance, we propose a metaheuristic optimization technique. The proposed technique is hybrid of two existing techniques: Tabu Search (TS) and bacterial foraging algorithm (BFA). The aim of the proposed technique is to reduce energy consumption so that user electricity bill reduces. Also, improves user comfort in term of average waiting time. For electricity bill calculation and appliance scheduling, time of use price tariff is used. Simulation results demonstrate that proposed scheme outperformed existing schemes in cost reduction and the average waiting time minimization. However, TS outruns other scheduling schemes in peak to average ratio reduction.
In this paper, the optimal power flow analysis is carried out using bacterial foraging algorithm for multi-objective function by considering security constrained and non-smooth cost function. The available capacities ...
详细信息
ISBN:
(纸本)9781467349215
In this paper, the optimal power flow analysis is carried out using bacterial foraging algorithm for multi-objective function by considering security constrained and non-smooth cost function. The available capacities of transmission lines are considered for wheeling transactions in the restructured electrical network and the transmission lines are checked for congestion. If there is any congestion then power producers is rescheduled by proposed approach. The proposed method is used to alleviate the congestion, improves the loadability and voltage stability, and reduces the line losses and cost of production by controlling the power flow in the network. And also congestion cost is calculated from the adjustments bids. The proposed method is demonstrated on IEEE 30 bus system and the results are to be compared with other optimization methods.
A healthy retina is required for proper vision but it is difficult to identify the retinal diseases in the first stage. Several retinal diseases affect the eye such as retinal tear, detachment of retina, glaucoma, mac...
详细信息
The proper maintenance plan should be made for ensuring the safety and reliability of polypropylene plant and improve economic benefits of petrochemical enterprise. To meet the requirement, a novel maintenance predict...
详细信息
The proper maintenance plan should be made for ensuring the safety and reliability of polypropylene plant and improve economic benefits of petrochemical enterprise. To meet the requirement, a novel maintenance prediction model of polypropylene plant based on fuzzy theory, ridgelet an artificial neural network is constructed. The economy and reliability models of polypropylene plant maintenance are established through comprehensively considering the reliability and economy. The basic structure of fuzzy ridgelet neural network is designed, and the training algorithm is improved through combining the traditional particle swarm algorithm and bacterial foraging algorithm, and the corresponding algorithm flow is confirmed. Finally, prediction simulation analysis is carried out using a polypropylene plant as research object, and analysis results show that the fuzzy ridgelet neural network has best prediction effect, and the optimal maintenance plan can be confirmed to ensure security and reduce maintenance cost of polypropylene plant.
Image segmentation is the method of partitioning an image into some homogenous regions that are more meaningful for its better understanding and examination. Soft computing methods having the capabilities of achieving...
详细信息
Image segmentation is the method of partitioning an image into some homogenous regions that are more meaningful for its better understanding and examination. Soft computing methods having the capabilities of achieving artificial intelligence are predominately used to perform the task of segmentation. Due to the variability and the uncertainty present in natural scenes, segmentation is a complicated task to perform with the help of conventional image segmentation techniques. Therefore, in this article a hybrid Fuzzy Competitive Learning based Counter Propagation Network (FCPN) is proposed for the segmentation of natural scene images. This method compromises of the uncertainty handling capabilities of the fuzzy system and proficiency of parallel learning ability of neural network. To identify the number of clusters automatically in less computational time, the instar layer of Counter propagation network (CPN) has been trained by using Fuzzy competitive learning (FCL). The outstar layer of counter propagation network is trained by using Grossberg learning for obtaining the desired output. Region growing method having the tendency to correctly identify edges with simplicity is used for initial seed point selection. Then, the most similar regions in the image are clustered and the number of clusters is estimated automatically. Finally, by identifying the cluster centers the images are segmented. bacterial foraging algorithm is used to initialize the initial weights to the network, which helps the proposed method in achieving low convergence ratio with higher accuracy. Results validated the higher performance of proposed FCPN method when compared with other states-of-the-art methods. For future work, some other adaptive methods like the fuzzy model-based network can be used to identify multiple object regions and classifying them among separate clusters.
Automatic appliances revamped the conventional electric systems by providing ease to complexity in activities of day today life. These appliances are smart, besides being energy efficient. Inefficient or poor illumina...
详细信息
ISBN:
(纸本)9789380544342
Automatic appliances revamped the conventional electric systems by providing ease to complexity in activities of day today life. These appliances are smart, besides being energy efficient. Inefficient or poor illumination results in wastage of financial resources and also creates unsafe conditions. Therefore, in order to minimize the electricity consumption, smart technology has to be implemented for lighting system. In this paper, remotely operated hardware system is designed along with a suitable interface via ESP8266 (Wi-Fi Wemos) for generating illumination patterns. Further, optimization of lighting system is performed by generating different light patterns. The effectiveness and efficiency of two nature inspired techniques viz. bacterialforaging optimization (BFO) and genetic algorithm (GA) are compared on the basis of different parameters like convergence rate, computational time, population size etc. Results obtained indicate that GA generates optimized patterns of illumination in less time and the energy saved by it is nearly 36% which is fairly efficient.
Generation landslide susceptibility maps are to study the relations among the image data of band variablesconcerning the occurrence/nonoccurrence on investigated samples of landslide. A feasible solution on generating...
详细信息
bacterial foraging algorithm (BFA) is one of the powerful bio-inspired optimization algorithms which attempt to imitate the single and groups of E. Coli bacteria. In BFA algorithm, a set of bacteria try to forage towa...
详细信息
bacterial foraging algorithm (BFA) is one of the powerful bio-inspired optimization algorithms which attempt to imitate the single and groups of E. Coli bacteria. In BFA algorithm, a set of bacteria try to forage towards a nutrient rich medium to get more nutrients. In this scheme, an objective function is posed as the effort or a cost incurred by the bacteria in search of food. In the present, an approach is presented for edge detection in a binarized image using bacterial foraging algorithm. .First binarization is applied to the input image to get an image matrix consisting of only the intensity values 0 and 255 of 8-bit image and then a swarm of bacteria are enthrusted on the binary image for extraction of edge information. Edges are detected by calculating the difference between intensity values of the present pixel with each of the neighboring eight pixels. Whenever the bacteria finds this intensity difference of 255 it will treat that pixel as its food and mark it as an edge pixel.
A method based on the bacterial foraging algorithm (BFA) for the pattern synthesis of linear antenna arrays with the prescribed nulls is presented. Nulling of the pattern is achieved by controlling only the element po...
详细信息
A method based on the bacterial foraging algorithm (BFA) for the pattern synthesis of linear antenna arrays with the prescribed nulls is presented. Nulling of the pattern is achieved by controlling only the element positions. The BFA is a new evolutionary computing technique, based on the foraging behavior of Escherichia (E) coli bacteria in a human intestine. Simulation results for Chebyshev patterns with the imposed single, multiple and broad nulls are given to show the effectiveness of the proposed method. For practical consideration, due to small variations of the element positions, the sensitivity of the produced patterns is also examined by rounding the element position values to the second decimal position.
At present,the takeout delivery platform pays more attention to the repurchase rate,so it needs to improve customer satisfaction to increase customer *** paper designs a non-linear penalty cost function to simulate th...
详细信息
At present,the takeout delivery platform pays more attention to the repurchase rate,so it needs to improve customer satisfaction to increase customer *** paper designs a non-linear penalty cost function to simulate the impact of overtime delivery on customer *** on the consideration of travelling cost and penalty cost,a mixed integer programming model is established,which is solved by an improved ant colony algorithm combined with bacterialforaging *** example is given to show that the new hybrid algorithm can obviously improve the search efficiency and the quality of the solution by the reproduction and elimination-dispersal ***,the transition probability is improved to accelerate the convergence speed and meet the characteristics of takeout delivery ***,the effectiveness and reliability of the improved hybrid algorithm are proved by comparing different algorithms through experiments.
暂无评论