Area optimization of parallel Chien search architecture for Reed-Solomon(255,239) decoder

A global optimization algorithm （GOA） for parallel Chien search circuit in Reed-Solomon （RS） （255,239） decoder is presented. By finding out the common modulo 2 additions within groups of Galois field （GF） multipliers and pre-computing the common items, the GOA can reduce the number of XOR gates efficiently and thus reduce the circuit area. Different from other local optimization algorithms, the GOA is a global one. When there are more than one maximum matches at a time, the best match choice in the GOA has the least impact on the final result by only choosing the pair with the smallest relational value instead of choosing a pair randomly. The results show that the area of parallel Chien search circuits can be reduced by 51% compared to the direct implementation when the group-based GOA is used for GF multipliers and by 26% if applying the GOA to GF multipliers separately. This optimization scheme can be widely used in general parallel architecture in which many GF multipliers are involved.

Optimization of Air Route Network Nodes to Avoid ″Three Areas″ Based on An Adaptive Ant Colony Algorithm

Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective function,and an air route network node(ARNN)optimization model was developed to circumvent the restrictions imposed by″three areas″,also known as prohibited areas,restricted areas,and dangerous areas(PRDs),by creating agrid environment.And finally the objective function was solved by means of an adaptive ant colony algorithm(AACA).The A593,A470,B221,and G204 air routes in the busy ZSHA flight information region,where the airspace includes areas with different levels of PRDs,were taken as an example.Based on current flight patterns,a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs.The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%.

Agricultural Production Structure Optimization: A Case Study of Major Grain Producing Areas, China

A large number of mathematical models were developed for supporting agricultural production structure optimization decisions; however, few of them can address various uncertainties existing in many factors （e.g., eco-social benefit maximization, food security, employment stability and ecosystem balance）. In this study, an interval-probabilistic agricultural production structure optimization model （IPAPSOM） is formulated for tackling uncertainty presented as discrete intervals and/or probability distribution. The developed model improves upon the existing probabilistic programming and inexact optimization approaches. The IPAPSOM considers not only food security policy constraints, but also involves rural households’income increase and eco-environmental conversation, which can effectively reflect various interrelations among different aspects in an agricultural production structure optimization system. Moreover, it can also help examine the reliability of satisfying （or risk of violating） system constraints under uncertainty. The model is applied to a real case of long-term agricultural production structure optimization in Dancheng County, which is located in Henan Province of Central China as one of the major grain producing areas. Interval solutions associated with different risk levels of constraint violation are obtained. The results are useful for generating a range of decision alternatives under various system benefit conditions, and thus helping decision makers to identify the desired agricultural production structure optimization strategy under uncertainty.

Industrial and Agricultural Effects on Water Environment and Its Optimization in Heavily Polluted Area in Taihu Lake Basin, China

The deteriorating water quality in the Taihu Lake Basin has attracted widespread attention for many years, and is correlated with a sharp increase in the quantity of pollutant discharge such as agricultural fertilizers and industrial wastewater. In this study, several factors were selected for evaluating and regionalizing the water environmental capacity by ArcG1S spatial analysis, including geomor- phologic characteristics, water quality goals, water body accessibility, water-dilution channels, and current water quality. Then, the spa- tial optimization of agriculture and industry was adjusted through overlay analysis, based on the balance between industrial space and water environmental capacity. The results show that the water environmental capacity gradually decreases from the west to the east, in contrast, the pollution caused by industrial and agricultural clustering is distributes along Taihu Lake, Gehu Lake and urban districts. The analysis of the agricultural space focuses on optimizing key protected areas of the Taihu Lake Basin, and the shores of Gehu Lake, optimally adjusting the second protected areas of the Taihu Lake Basin, and generally adjusting the urban areas of Changzhou and Wuxi cities. The analysis of industrial space focuses on optimizing the downtowns of Changzhou and Wuxi cities, optimally adjusting key protected areas and second protected areas of the Taihu Lake Basin, and generally adjusting the south and southwest of Gehu Lake. Lastly, some schemes of industrial and agricultural layouts and policies for the direction of industrial and agricultural development were proposed, reflecting a correlation between industry and agriculture and the water environment.

Online task planning method of anti-ship missile based on rolling optimization

Based on the wave attack task planning method in static complex environment and the rolling optimization framework, an online task planning method in dynamic complex environment based on rolling optimization is proposed. In the process of online task planning in dynamic complex environment,online task planning is based on event triggering including target information update event, new target addition event, target failure event, weapon failure event, etc., and the methods include defense area reanalysis, parameter space update, and mission re-planning. Simulation is conducted for different events and the result shows that the index value of the attack scenario after re-planning is better than that before re-planning and according to the probability distribution of statistical simulation method, the index value distribution after re-planning is obviously in the region of high index value, and the index value gap before and after re-planning is related to the degree of posture change.

Scheduling optimization for UAV communication coverage using virtual force-based PSO model

When the ground communication base stations in the target area are severely destroyed,the deployment of Unmanned Aerial Vehicle(UAV)ad hoc networks can provide people with temporary communication services.Therefore,it is necessary to design a multi-UAVs cooperative control strategy to achieve better communication coverage and lower energy consumption.In this paper,we propose a multi-UAVs coverage model based on Adaptive Virtual Force-directed Particle Swarm Optimization(AVF-PSO)strategy.In particular,we first introduce the gravity model into the traditional Particle Swarm Optimization(PSO)algorithm so as to increase the probability of full coverage.Then,the energy consumption is included in the calculation of the fitness function so that maximum coverage and energy consumption can be balanced.Finally,in order to reduce the communication interference between UAVs,we design an adaptive lift control strategy based on the repulsion model to reduce the repeated coverage of multi-UAVs.Experimental results show that the proposed coverage strategy based on gravity model outperforms the existing state-of-the-art approaches.For example,in the target area of any size,the coverage rate and the repeated coverage rate of the proposed multi-UAVs scheduling are improved by 6.9–29.1%,and 2.0–56.1%,respectively.Moreover,the proposed scheduling algorithm is high adaptable to diverse execution environments.©2022 Published by Elsevier Ltd.

Characteristics and Optimization of Distribution of Rural Residential Area in Wangcun River Basin of Linfen City

As a carrier of rural population,rural residential area carries important functions such as rural production and life. This paper studied the characteristics of rural residential area and optimization model,to lay certain foundation for integrating urban and rural development and increasing economic income. With the aid of Arc GIS 10. 1 and Fragstats 3. 4 software,based on the theory of landscape ecology,it analyzed the distribution characteristics of residential area in Wangcun River Basin of Anze County,Linrfen City,Shanxi Province. Besides,according to distribution characteristics,it analyzed three optimization models: priority development model,retention limit development model,and migration development model.

Study of the Optimization and Adjustment ofthe IndustrialStructure Subjected to Water Resource in the Drainage Area of the Yellow River

Since the 1990s, the Yellow River stream has been temporarily interrupted for several years, which affects the development of society, the economy and human life, limits the economic potential of the drainage areas, and especially causes great harm to regions on the lower reaches. Based on the analysis of the relationship between the development of society and economy and water scarcity, the author thinks it is necessary to optimize and adjust the industrial structure that has extravagantly consumed enormous amounts of water, and to develop ecological agriculture, industry and tourism which are balanced with the ecological environment. Finally, the author puts forward several pieces of advice and countermeasures about how to build the economic systems by which water can be used economically.

Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm

In this study, we present a Pareto-based chemicalreaction optimization(PCRO) algorithm for solving the multiarea environmental/economic dispatch optimization problems.Two objectives are minimized simultaneously, i.e., total fuel cost and emission. In the proposed algorithm, each solution is represented by a chemical molecule. A novel encoding mechanism for solving the multi-area environmental/economic dispatch optimization problems is designed to dynamically enhance the performance of the proposed algorithm. Then, an ensemble of effective neighborhood approaches is developed, and a selfadaptive neighborhood structure selection mechanism is also embedded in PCRO to increase the search ability while maintaining population diversity. In addition, a grid-based crowding distance strategy is introduced, which can obviously enable the algorithm to easily converge near the Pareto front. Furthermore,a kinetic-energy-based search procedure is developed to enhance the global search ability. Finally, the proposed algorithm is tested on sets of the instances that are generated based on realistic production. Through the analysis of experimental results, the highly effective performance of the proposed PCRO algorithm is favorably compared with several algorithms, with regards to both solution quality and diversity.

Multi-Objective Bacterial Foraging Optimization Algorithm Based on Effective Area in Cognitive Emergency Communication Networks

Cognitive emergency communication net-works can meet the requirements of large capac-ity,high density and low delay in emergency com-munications.This paper analyzes the properties of emergency users in cognitive emergency communi-cation networks,designs a multi-objective optimiza-tion and proposes a novel multi-objective bacterial foraging optimization algorithm based on effective area(MOBFO-EA)to maximize the transmission rate while maximizing the lifecycle of the network.In the algorithm,the effective area is proposed to prevent the algorithm from falling into a local optimum,and the diversity and uniformity of the Pareto-optimal solu-tions distributed in the effective area are used to eval-uate the optimization algorithm.Then,the dynamic preservation is used to enhance the competitiveness of excellent individuals and the uniformity and diversity of the Pareto-optimal solutions in the effective area.Finally,the adaptive step size,adaptive moving direc-tion and inertial weight are used to shorten the search time of bacteria and accelerate the optimization con-vergence.The simulation results show that the pro-posed MOBFO-EA algorithm improves the efficiency of the Pareto-optimal solutions by approximately 55%compared with the MOPSO algorithm and by approx-imately 60%compared with the MOBFO algorithm and has the fastest and smoothest convergence.

“City-Scene” Characteristics and Optimization Strategies Research on Three Gorges Reservoir Area of the Post-Three Gorges Era

In the long-term symbiotic evolution process,the town areas along the Yangtze River and its natural and cultural landscapes have presented a sound "city-scene" landscape form. But with the implementation of the Three Gorges project,the town relocation as well as the flooding in the natural and human landscape area,the original harmonious "city-scene" pattern started to collapse and fell into the situation of "fragmentation" and "islanding". The differentiation between city and landscape,uncoordinated scale and fractured urban context become pressing issues that affect the integral form optimization of the town areas. This paper aims at responding to the call of the government about proceeding the construction of the Yangtze River economic belt under the ecological and green strategy and seeking an attuned "cityscene" relationship of the town area. Based on the analysis of the dynamic evolution of the "city-scene" relationship,the paper also pointed out that the urban construction around the reservoir area in the postThree Gorges era was the key stage of "scene-city" integration and symbiosis while the maintenance of scenery pattern,the harmony of space scale and the protection of living culture should be applied as the vital strategies.

The Evolution of Landscape Patterns of and Optimization Measures for Urban Core Areas Against the Background of Urbanization: A Case Study of Yangling Demonstration Zone

Studying tiie urban landscape pattern plays a crucial role in scientific land use and management and in improving the urban ecological environment In this paper, AutoCAD, ArcGIS, Fragstats, and other software were used to analyse the data of the fourth phase of land use in the core atea of Yangling Demonstration Zone. The results showed that： ① in the core area, the percentage of construction land incteased from 18.22% to 61.72%, and the percentage of agricultufal land decreased from 58.36% to 11.14%. And the fafm land was fragmented, and traffic connectivily was strengthened. The afea of garden land was reduced from 251.89 hm2 to 50.38 hm^2, and the landscape metric of forest land showed an inverted V-shaped curve. ②The year 2009 in four phases witnessed the greatest landscape fragmentation, both Edge Density （ED） and Ingest Patch Index （LPI） increased, and human interference enhanced the overall landscape complexity. Measures were fotmulated in terms of deaf development goals, optimized allocation of land resoutces, effective protection of ecological ted lines, and definite ecological responsibility, so as to optimize the urban landscape pattern.

Investigation and Optimization of Priority for Non-motor Vehicles in the Old Urban Area of Nanchang

Under the background of"people-oriented"thought and"green transportation",the idea of"priority for non-motor vehicles"came into being,which can improve the riding environment of non-motor vehicle riders to a certain extent.According to the current situation of priority for non-motor vehicles in the old urban area of Nanchang,through field investigation,questionnaire investigation and interview,this study summarized the existing problems,and put forward optimization suggestions for these problems,in order to provide reference for areas with similar conditions.

Tourism Spatial Structure in Urban Agglomeration of the Greater Bay Area and Its Optimization

With the rapid development of economy,China’s urbanization process is accelerated.As major urban cluster center,Guangdong-Hong Kong-Macao Greater Bay Area is regarded as one of the most representative areas with the highest openness and the strongest economic vitality.Under the background of new era,main purpose of making development strategy of the Greater Bay Area is to build a world-class city cluster with great vitality,and establish a world-class science and technology innovation center with great influence.It also lays a good foundation for strengthening the construction of the belt and road initiative in China,and improves quality of life in the cooperation zone between the mainland and Hong Kong and Macao.Under the background,the tourism industry has new challenges,and the tourism spatial structure should be more closely linked.In this paper,tourism spatial structure of 9+2 urban agglomeration in the Greater Bay Area is taken as core research objective,and tourism resource of the urban agglomeration,and development of tourism economy and perfect transportation network in each city are analyzed.According to research results,the targeted suggestions and optimization methods are obtained.

Sensitivity Assessment and Optimization Strategy of Climatic Environment in Central Urban Area of Beijing

As one of the methods of urban environmental assessment,sensitivity assessment of urban climatic environment can accurately reflect the problem areas of current urban climate and built environment through visual means,and help cities to carry out sustainable transformation and renewal in the stock era to optimize the living environment.Taking the central urban area of Beijing as the research object,the sensitivity of climatic environment was evaluated by meteorological data and built environment element data.The results showed that the distribution of sensitive units showed a centrifugal radiation pattern of"high in the center and low in the periphery".Block units with high climate sensitivity were mostly concentrated in Xicheng District and Dongcheng District,accounting for 93%of the total number of units.Further research showed that complex built environment and lack of elements to regulate climatic environment were the main reasons for the poor local climatic environment in the region with high climate sensitivity.Finally,a comprehensive evaluation of the remolding capacity,renewal potential and future development intensity of different grades of climate sensitive units was given.The results will provide scientific reference for urban renewal and reconstruction under climatic and environmental changes,so as to promote urban sustainable development and improvement of living environment.

Algorithmic Optimization of BDDs and Performance Evaluation for Multi-level Logic Circuits with Area and Power Trade-offs

Binary Decision Diagrams (BDDs) can be graphically manipulated to reduce the number of nodes and hence the area. In this context, ordering of BDDs play a major role. Most of the algorithms for input variable ordering of OBDD focus primarily on area minimization. However, suitable input variable ordering helps in minimizing the power consumption also. In this particular work, we have proposed two algorithms namely, a genetic algorithm based technique and a branch and bound algorithm to find an optimal input variable order. Of course, the node reordering is taken care of by the standard BDD package buddy-2.4. Moreover, we have evaluated the performances of the proposed algorithms by running an exhaustive search program. Experi-mental results show a substantial saving in area and power. We have also compared our techniques with other state-of-art techniques of variable ordering for OBDDs and found to give superior results.

Ant Lion Optimization Approach for Load Frequency Control of Multi-Area Interconnected Power Systems

This work proposes a novel nature-inspired algorithm called Ant Lion Optimizer (ALO). The ALO algorithm mimics the search mechanism of antlions in nature. A time domain based objective function is established to tune the parameters of the PI controller based LFC, which is solved by the proposed ALO algorithm to reach the most convenient solutions. A three-area interconnected power system is investigated as a test system under various loading conditions to confirm the effectiveness of the suggested algorithm. Simulation results are given to show the enhanced performance of the developed ALO algorithm based controllers in comparison with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bat Algorithm (BAT) and conventional PI controller. These results represent that the proposed BAT algorithm tuned PI controller offers better performance over other soft computing algorithms in conditions of settling times and several performance indices.

Optimal livelihood strategy for different poverty groups among farmers: a case study of the Qin-Ba Mountain area in South-Shaanxi, China

Achieving sustainable livelihood is the ultimate goal of poverty alleviation efforts in mountainous areas,and selecting an optimal livelihood strategy for different poverty-type farmers greatly improves farmers’livelihood capital,resists livelihood risks,and promotes sustainable development.For farmers,optimal livelihood strategy means better employment opportunities,higher family income(or better income structure),and stronger employability or development potential.This paper classifies different types of farmers’poverty on the basis of a quantitative evaluation of farmers’livelihood capital in the Qin-ba Mountain Area in South-Shaanxi by using the k-means clustering method and subsequently the fuzzy evaluation method to evaluate the effectiveness of farmers’livelihood strategies.Then,the multi-attribute decision-making model is used to analyze the selection of optimal livelihood strategies for different poverty-type farmers.The results suggest a significant difference in the selection of the optimal livelihood strategy for different poverty-type farmers.Farmers without financial and human capital choose to"go out to work,"farmers lacking natural capital choose to"acquire social insurance and government relief,"farmers without physical capital choose to"use loans,"and farmers lacking social capital choose to"use savings."Studying the selection of optimal livelihood strategies for different poverty-type farmers can help to propose targeted sustainable livelihood optimization programs for farmers and accelerate efforts to overcome poverty in mountainous areas.

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.