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With the construction of smart grids, smart meters are gradually being installed in every house. In order to transfer the user data collected by smart meters to the control center, it is necessary to transfer the data to the data aggregation point (DAP) before being transmitted to the control center. The numbers and locations of DAPs affect the communication quality and cost of the smart meter neighborhood network, and because smart meters rely on wireless technology to transmit data, their transmission range is limited. Thus, suburban and rural areas require a large number of DAP installation needs, and it is very important to reduce their numbers. For this problem, this study proposes a grid-based relay DAP placement scheme and presents the corresponding algorithms to reduce the number of DAPs and to avoid the large impact of relay DAP locations on communication quality for the two cases of whether or not the number of relay DAPs is limited. This paper used random smart meter coordinates for testing, and the test results verify that the proposed solution can in fact significantly reduce the number of DAPs and avoid the large impact of relay DAP locations on communication quality.

Social science education aims to enable people to acquire the knowledge and abilities necessary to lead a normal social life. However, social science is often neglected in basic education compared ...

The Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is a swarm-based collaborative optimization algorithm, which has drawn attention from researchers due to its simple structure, easy implementation, and powerful performance. However, it needs to be improved regarding the exploration, especially in the late stage of evolution, and the problem of easy falling into a local optimal solution. This paper proposes an improved algorithm named Quasi-Affine Transformation Evolutionary with double excellent guidance (QUATRE-DEG). The algorithm uses not only the global optimal solution but also the global suboptimal solution to guide the individual evolution. We establish a model to determine the guiding force by the distance between the global optimal position and the suboptimal position and propose a new mutation strategy through the double population structure. The optimization of population structure and the improvement of operation mechanisms bring more exploration for the algorithm. To optimize the algorithm, the experiments on parameter settings were made to determine the size of the subpopulation and to achieve a balance between exploration and development. The performance of QUATRE-DEG algorithm is evaluated under CEC2013 and CEC2014 test suites. Through comparison and analysis with some ABC variants known for their strong exploration ability and advanced QUATRE variants, the competitiveness of the proposed QUATRE-DEG algorithm is validated.

The artificial bee colony (ABC) algorithm is one of the classical bioinspired swarm-based intelligence algorithms that has strong search ability, because of its special search mechanism, but its development ability is slightly insufficient and its convergence speed is slow. In view of its weak development ability and slow convergence speed, this paper proposes the QABC algorithm in which a new search equation is based on the idea of quasi-affine transformation, which greatly improves the cooperative ability between particles and enhances its exploitability. During the process of location updating, the convergence speed is accelerated by updating multiple dimensions instead of one dimension. Finally, in the overall search framework, a collaborative search matrix is introduced to update the position of particles. The collaborative search matrix is transformed from the lower triangular matrix, which not only ensures the randomness of the search, but also ensures its balance and integrity. To evaluate the performance of the QABC algorithm, CEC2013 test set and CEC2014 test set are used in the experiment. After comparing with the conventional ABC algorithm and some famous ABC variants, QABC algorithm is proved to be superior in efficiency, development ability, and robustness.

The WSN uses wireless communication to realize its information transmission. WSN is a network data system composed of a large number of wireless data collectors with sensing functions. In the WSN-based sensing function structure, the size should be small, more power saving, low price, and can achieve design goals. This study first assumes that WSN uses routing algorithm assumptions in the protocol, and starts from the node position and direction information, and considers the dynamic evolution of the network. Each public node has random mobility, and the WSN node can help determine the location information of the public node, and then use the node location information to have effective routing performance and effective. However, the experimental results also strongly support the energy saving ability of this research. In the overall system energy saving and power consumption reduction, the actual electric energy hazard is greatly reduced, so in the spirit of ISD strategies, if the WSN system is installed in a high-risk and explosive atmosphere, it can significantly improve the safety level.

In recent years, evolutionary algorithms based on swarm intelligence have drawn much attention from researchers. This kind of artificial intelligent algorithms can be utilized for various applications, including the ones of big data information processing in nowadays modern world with heterogeneous sensor and IoT systems. Differential evolution (DE) algorithm is one of the important algorithms in the field of optimization because of its powerful and simple characteristics. The DE has excellent development performance and can approach global optimal solution quickly. At the same time, it is also easy to get into local optimal, so it could converge prematurely. In the view of these shortcomings, this article focuses on the improvement of the algorithm of DE and proposes an adaptive dimension differential evolution (ADDE) algorithm that can adapt to dimension updating properly and balance the search and the development better. In addition, this article uses the elitism to improve the location update strategy to improve the efficiency and accuracy of the search. In order to verify the performance of the new ADDE, this study carried out experiments with other famous algorithms on the CEC2014 test suite. The comparison results show that the ADDE is more competitive.

In terms of fire outbreak, the nature of some big industries and thermal plants seems extremely volatile. The existence of oxygen and fuel cannot be taken out in thermal power plant, and many actions may be originated from heat source. Many researchers have developed more interest in the research field of fire detection in some big industries and thermal plants, especially those who use hydrocarbon-based product as fuel. The fire that normally occurs at these places is normally class B type of fire, and carbon dioxide is used to put them off. This paper proposes a design of an automated fire alarm system which utilizes already existing technologies such as the wireless sensor network technology and carbon capture and storage system to help alleviate the problem of global warming and reduce the cost incurred in existing ineffective fire alarm system. During combustion process in the thermal plant, the carbon dioxide emitted is captured and stored to be used to put off or suppressing fire after early detection by the wireless sensor network with sensors such as optical flame detectors, heat detector, and hydrogen detector. The simulations done on the final designs proved that this system is feasible and can be successfully deployed on a larger scale.

As the current computer design level continues to improve, the process equipment and production line management levels are relatively stable. The intelligent and automatic 3D garage-type has shown a diversified development trend. Several garage types are currently in everyday use, including vertical lifting type, vertical lifting type, simple lifting type, horizontal shifting circulation type, channel stacking type, etc. The 3D lifting garage has a simple structure, small floor space, low operating cost, and the most extensive application requirements. However, this study summarizes the application status and development prospects of smart lifting 3D garages first. Then the system analyzes the working principle and mechanical structure characteristics of the smart lifting 3D garage, analyzes the control requirements, and designs the semi-automatic control system of the 3D garage S7–1200—it including the PLC control program and the man-machine interface. Finally, the overall system control effect is verified through simulation. This study meter has superficial operation characteristics, a high degree of automation, fast operation speed, high stability, and has deep development value and application prospects in specific markets.

There are incredibly renewable outlets such as solar and wind intermittent, and machine reliability is hard to sustain with the intolerable balance of green energy resources. Because of population growth and technological development, global energy demand is increasing exponentially. However, civilization must address a stable energy source for two benefits, a cost-effective and sustainable basis for future renewable energy production. Solar Energy is a platform for green energy and is a potential means of solving problems that face a possible energy system. The power output is primarily determined by the properties of the incoming radiation and solar panels. Precise and accurate knowledge of these variables provides a consistent model for predicting the solar future. Solar power forecasts would have a significant effect on the viability of massive solar energy projects. This study presents a new approach to predict the expected amount of energy to be produced from Photovoltaics using a hybrid deep neural network based on a combination of extended short-term memory networks (LSTM) and convolutional neural networks (CNN), taking into account the energy of electrons and photons as well as elements and climatic conditions as input data.

There are several important steps in modern wafer manufacturing: oxidation, deposition, lithography, etching, ion implantation, diffusion, etc. Metal organic chemical vapor deposition (MOCVD) is one of the most commonly used CVD techniques for thin film deposition in integrated circuits. MOCVD is a new technology for manufacturing high-quality integrated circuit films. In order to make the MOCVD system work properly, we need to accurately control the parameters of the process (pressure, temperature, flow). In this study, a Simulink toolbox of MATLAB was used to simulate the control object of MOCVD, and to obtain the incremental PID algorithm and control results. It is found that the adjustment of the system timeout is not effective because of the long adjustment time. However, this research using the Smith predictor is added to optimize the control effect and improve the controller; reduce the adjustment time of the system; adjust the system timeout to zero; and have better control efficiency in the pressure, flow, and temperature control system, and this is an important breakthrough in this research.