TREEVIEW只输入表名,父ID,节点ID,节点名就得到树型结构之十四(转)

本文介绍了如何使用C#通过SqlConnection和SqlTransaction执行SQL存储过程,返回1x1结果集的方法。包括两种重载方法,一种直接接收SqlParameter数组,另一种通过参数名和值自动分配SqlParameter。这些方法有助于简化数据库交互代码。
///
/// Execute a SqlCommand (that returns a 1x1 resultset) against the specified SqlTransaction
/// using the provided parameters.
///
///
/// e.g.:
/// int orderCount = (int)ExecuteScalar(trans, CommandType.StoredProcedure, "GetOrderCount", new SqlParameter("@prodid", 24));
///
/// A valid SqlTransaction
/// The CommandType (stored procedure, text, etc.)
/// The stored procedure name or T-SQL command
/// An array of SqlParamters used to execute the command
/// An object containing the value in the 1x1 resultset generated by the command
public static object ExecuteScalar(SqlTransaction transaction, CommandType commandType, string commandText, params SqlParameter[] commandParameters)
{
if( transaction == null ) throw new ArgumentNullException( "transaction" );
if( transaction != null && transaction.Connection == null ) throw new ArgumentException( "The transaction was rollbacked or commited, please provide an open transaction.", "transaction" );

// Create a command and prepare it for execution
SqlCommand cmd = new SqlCommand();
bool mustCloseConnection = false;
PrepareCommand(cmd, transaction.Connection, transaction, commandType, commandText, commandParameters, out mustCloseConnection );

// Execute the command & return the results
object retval = cmd.ExecuteScalar();

// Detach the SqlParameters from the command object, so they can be used again
cmd.Parameters.Clear();
return retval;
}

///
/// Execute a stored procedure via a SqlCommand (that returns a 1x1 resultset) against the specified
/// SqlTransaction using the provided parameter values. This method will query the database to discover the parameters for the
/// stored procedure (the first time each stored procedure is called), and assign the values based on parameter order.
///
///
/// This method provides no access to output parameters or the stored procedure's return value parameter.
///
/// e.g.:
/// int orderCount = (int)ExecuteScalar(trans, "GetOrderCount", 24, 36);
///
/// A valid SqlTransaction
/// The name of the stored procedure
/// An array of objects to be assigned as the input values of the stored procedure
/// An object containing the value in the 1x1 resultset generated by the command
public static object ExecuteScalar(SqlTransaction transaction, string spName, params object[] parameterValues)
{
if( transaction == null ) throw new ArgumentNullException( "transaction" );
if( transaction != null && transaction.Connection == null ) throw new ArgumentException( "The transaction was rollbacked or commited, please provide an open transaction.", "transaction" );
if( spName == null || spName.Length == 0 ) throw new ArgumentNullException( "spName" );

// If we receive parameter values, we need to figure out where they go
if ((parameterValues != null) && (parameterValues.Length > 0))
{
// PPull the parameters for this stored procedure from the parameter cache (or discover them & populate the cache)
SqlParameter[] commandParameters = SqlHelperParameterCache.GetSpParameterSet(transaction.Connection, spName);

// Assign the provided values to these parameters based on parameter order
AssignParameterValues(commandParameters, parameterValues);

// Call the overload that takes an array of SqlParameters
return ExecuteScalar(transaction, CommandType.StoredProcedure, spName, commandParameters);
}
else
{
// Otherwise we can just call the SP without params
return ExecuteScalar(transaction, CommandType.StoredProcedure, spName);
}
}

#endregion ExecuteScalar

[@more@]

来自 “ ITPUB博客 ” ,链接:http://blog.itpub.net/8781179/viewspace-924797/,如需转载,请注明出处,否则将追究法律责任。

转载于:http://blog.itpub.net/8781179/viewspace-924797/

【无人机】基于改进粒子群算法的无人机路径规划研究[和遗传算法、粒子群算法进行比较](Matlab代码实现)内容概要:本文围绕基于改进粒子群算法的无人机路径规划展开研究,重点探讨了在复杂环境中利用改进粒子群算法(PSO)实现无人机三维路径规划的方法,并将其与遗传算法(GA)、标准粒子群算法等传统优化算法进行对比分析。研究内容涵盖路径规划的多目标优化、避障策略、航路点约束以及算法收敛性和寻优能力的评估,所有实验均通过Matlab代码实现,提供了完整的仿真验证流程。文章还提到了多种智能优化算法在无人机路径规划中的应用比较,突出了改进PSO在收敛速度和全局寻优方面的优势。; 适合人群:具备一定Matlab编程基础和优化算法知识的研究生、科研人员及从事无人机路径规划、智能优化算法研究的相关技术人员。; 使用场景及目标:①用于无人机在复杂地形或动态环境下的三维路径规划仿真研究;②比较不同智能优化算法(如PSO、GA、蚁群算法、RRT等)在路径规划中的性能差异;③为多目标优化问题提供算法选型和改进思路。; 阅读建议:建议读者结合文中提供的Matlab代码进行实践操作,重点关注算法的参数设置、适应度函数设计及路径约束处理方式,同时可参考文中提到的多种算法对比思路,拓展到其他智能优化算法的研究与改进中。
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